{ "metadata": { "name": "", "signature": "sha256:8c5ed5c88bf3946e32edf6666deb431b5a307bd2192a14386a8ff6b70c73f8fc" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "code", "collapsed": false, "input": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "\n", "# Some nice default configuration for plots\n", "plt.rcParams['figure.figsize'] = 10, 7.5\n", "plt.rcParams['axes.grid'] = True\n", "plt.gray()\n", "\n", "import numpy as np\n", "import pandas as pd" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "text": [ "" ] } ], "prompt_number": 55 }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "6. Linear Regression and Its Cousins" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will dicuss several models here, all of which are akin to linear regression in that each can directly or indirectly be written in the form\n", "$$y_i = \\beta_0 + \\beta_1 x_{i1} + \\cdots + \\beta_p x_{ip} + \\epsilon_i,$$\n", "where $y_i$ represents the numeric response for the $i$th sample, $\\beta_0$ represents the estimated intercept, $\\beta_j$ represents the estimated coefficient for the $j$th predictor, $x_{ij}$ represents the value of the $j$th predictor for the $i$th sample, and $\\epsilon_i$ represents random error that cannot be explained by the model. In addition to ordinary linear regression, these types of models include partial least square (PLS) and penalized models such as ridge regression, the lasso, and the elastic net.\n", "\n", "Each of these models seek to find estimates of the parameters so that the sum of squared errors or a function of the sum of squared errors is minimized. The objectives of the methods find parameter estimates that fall along the spectrum of the bias-variance trade-off. Ordinary linear regression, at one extreme, finds parameter estimates that have minimum bias, where ridge regression, the lasso, and the elastic net find estimates that have lower variance.\n", "\n", "A distinct advantage of linear regression models is that they are highly interpretable. Furthermore, relationships among predictors can be further interpreted through the estimated coefficients. Another advantage is that their mathematrical nature enables us to compute standard errors of the coefficients, provided that we make certain assumptions about the distribution of the model residuals.\n", "\n", "While linear regression-type models are highly interpretable, they can be limited in their usefulness. First, these models are appropriate when the relationship between the predictors and response falls along a hyperplane. If there is a curvilinear relationship between the predictors and response, then linear regression models can be augmented with additional predictors that are functions of the original predictors in an attempt to capture these relationships." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "6.1 Case Study: Quantitative Structure-Acitivity Relationship Modeling" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The study investigated a set of compounds with corresponding experimental solubility values using complex sets of descriptors. We will use 1,267 compounds (951 training and 316 test by random sampling) and a set of more understandable descriptors:\n", "- Two hundred and eight binary \"fingerprints\" that indicate the presence or absence of a particular chemical substructure.\n", "- Sixteen count descriptors, such as the number of bonds or the number of bromine atoms.\n", "- Four continuous descriptors, such as molecular weight or surface area.\n", "\n", "The training set will be used to tune and estimate models, as well as to determine initial estimates of performance using repeated 10-fold cross-validation. The test set will be used for a final characterization of the model of interest." ] }, { "cell_type": "code", "collapsed": false, "input": [ "!ls -l ../datasets/solubility/" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "total 3016\r\n", "-rw-r--r-- 1 leigong staff 153513 Nov 24 15:58 solTestX.csv\r\n", "-rw-r--r-- 1 leigong staff 226232 Nov 24 15:58 solTestXtrans.csv\r\n", "-rw-r--r-- 1 leigong staff 2996 Nov 24 15:58 solTestY.csv\r\n", "-rw-r--r-- 1 leigong staff 459104 Nov 24 15:58 solTrainX.csv\r\n", "-rw-r--r-- 1 leigong staff 679218 Nov 24 15:58 solTrainXtrans.csv\r\n", "-rw-r--r-- 1 leigong staff 9202 Nov 24 15:58 solTrainY.csv\r\n" ] } ], "prompt_number": 56 }, { "cell_type": "code", "collapsed": false, "input": [ "# training\n", "trainX = pd.read_csv(\"../datasets/solubility/solTrainX.csv\").drop(\"Unnamed: 0\", axis=1)\n", "trainY = pd.read_csv(\"../datasets/solubility/solTrainY.csv\").drop(\"Unnamed: 0\", axis=1)\n", "\n", "# test \n", "testX = pd.read_csv(\"../datasets/solubility/solTestX.csv\").drop(\"Unnamed: 0\", axis=1)\n", "testY = pd.read_csv(\"../datasets/solubility/solTestY.csv\").drop(\"Unnamed: 0\", axis=1)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 57 }, { "cell_type": "code", "collapsed": false, "input": [ "trainX.head(5)" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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FP001FP002FP003FP004FP005FP006FP007FP008FP009FP010...NumCarbonNumNitrogenNumOxygenNumSulferNumChlorineNumHalogenNumRingsHydrophilicFactorSurfaceArea1SurfaceArea2
0 0 1 0 0 1 0 0 1 0 0... 14 2 0 0 0 0 3-0.856 25.78 25.78
1 0 1 0 1 1 1 1 1 0 0... 21 3 1 1 0 0 4-0.370 52.19 80.43
2 1 1 1 1 1 0 0 1 0 1... 13 0 2 0 0 0 1-0.330 37.30 37.30
3 0 0 1 0 0 0 1 0 0 0... 10 0 0 0 0 0 1-0.960 0.00 0.00
4 0 0 1 1 1 1 0 0 1 0... 9 5 0 0 1 1 1-0.069 53.94 53.94
\n", "

5 rows \u00d7 228 columns

\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 58, "text": [ " FP001 FP002 FP003 FP004 FP005 FP006 FP007 FP008 FP009 FP010 \\\n", "0 0 1 0 0 1 0 0 1 0 0 \n", "1 0 1 0 1 1 1 1 1 0 0 \n", "2 1 1 1 1 1 0 0 1 0 1 \n", "3 0 0 1 0 0 0 1 0 0 0 \n", "4 0 0 1 1 1 1 0 0 1 0 \n", "\n", " ... NumCarbon NumNitrogen NumOxygen NumSulfer NumChlorine \\\n", "0 ... 14 2 0 0 0 \n", "1 ... 21 3 1 1 0 \n", "2 ... 13 0 2 0 0 \n", "3 ... 10 0 0 0 0 \n", "4 ... 9 5 0 0 1 \n", "\n", " NumHalogen NumRings HydrophilicFactor SurfaceArea1 SurfaceArea2 \n", "0 0 3 -0.856 25.78 25.78 \n", "1 0 4 -0.370 52.19 80.43 \n", "2 0 1 -0.330 37.30 37.30 \n", "3 0 1 -0.960 0.00 0.00 \n", "4 1 1 -0.069 53.94 53.94 \n", "\n", "[5 rows x 228 columns]" ] } ], "prompt_number": 58 }, { "cell_type": "code", "collapsed": false, "input": [ "trainY.head(5)" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
0
0-3.97
1-3.98
2-3.99
3-4.00
4-4.06
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" ], "metadata": {}, "output_type": "pyout", "prompt_number": 59, "text": [ " 0\n", "0 -3.97\n", "1 -3.98\n", "2 -3.99\n", "3 -4.00\n", "4 -4.06" ] } ], "prompt_number": 59 }, { "cell_type": "code", "collapsed": false, "input": [ "print \"training set size: {0} \\ntest set size: {1}\".format(trainX.shape, testX.shape)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "training set size: (951, 228) \n", "test set size: (316, 228)\n" ] } ], "prompt_number": 60 }, { "cell_type": "code", "collapsed": false, "input": [ "print \"The range of the outcome is {0} with an avearge of {1}.\".format((round(np.min(trainY)[0], 2), \n", " round(np.max(trainY)[0], 2)),\n", " round(np.mean(trainY)[0], 2))" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "The range of the outcome is (-11.62, 1.58) with an avearge of -2.72.\n" ] } ], "prompt_number": 61 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Relationship between the outcome and two types of descriptors." ] }, { "cell_type": "code", "collapsed": false, "input": [ "fig, (ax1, ax2) = plt.subplots(1, 2)\n", "\n", "ax1.scatter(trainX['MolWeight'], trainY)\n", "ax1.set_xlabel(\"Molecular Weight\")\n", "ax1.set_ylabel(\"Solubility (log)\")\n", "\n", "trainY_strPresent = trainY.iloc[np.where(trainX['FP003'] == 1)[0]]\n", "trainY_strAbsent = trainY.iloc[np.where(trainX['FP003'] == 0)[0]]\n", "trainY_str = [trainY_strPresent, trainY_strAbsent]\n", "ax2.boxplot(trainY_str)\n", "ax2.set_xticklabels(['structure present', 'structure absent'])\n", "ax2.set_ylabel(\"Solubility (log)\")" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 62, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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HR6M15rEqcQ193eS53d3d43Z/xgO/2aOU/2wSezJj/j+f97lnPLbxnL+mGn77XgmTB3Tn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"text": [ "" ] } ], "prompt_number": 62 }, { "cell_type": "markdown", "metadata": {}, "source": [ "It is useful to explore the training set to understand the characteristics of the data prior to modeling." ] }, { "cell_type": "code", "collapsed": false, "input": [ "# evaluate the continuous predictors for skewness\n", "trainX_c = trainX[trainX.columns[-20:]] # continuous predictors\n", "\n", "from scipy.stats import skew\n", "trainX_skewness = trainX_c.apply(skew)\n", "print \"Summary of skewness: range {0}; mean {1}\".format((round(np.min(trainX_skewness), 2), \n", " round(np.max(trainX_skewness), 2)), \n", " round(np.mean(trainX_skewness), 2))" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Summary of skewness: range (0.67, 3.84); mean 1.65\n" ] } ], "prompt_number": 63 }, { "cell_type": "markdown", "metadata": {}, "source": [ "It indicates that these predictors have a propensity to be right skewed (skewness = 0 if normally distributed). To correct for this skewness, a Box-Cox transformation was applied to all predictors (add a shift parameter to non-positive predictors)." ] }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "Side note" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "One-parameter Box-Cox transformations (for x > 0)\n", "\$$\n", "x^* = \\begin{cases} {x^{\\lambda}-1 \\over \\lambda} & \\text{if} \\ \\lambda \\neq 0 \\\\ log(x) & \\text{if} \\ \\lambda = 0 \\end{cases}\n", "\$$\n", "\n", "Two-parameter Box-Cox transformations (for x > $\\lambda_2$)\n", "\$$\n", "x^* = \\begin{cases} {(x+\\lambda_2)^{\\lambda_1}-1 \\over \\lambda_1} & \\text{if} \\ \\lambda_1 \\neq 0 \\\\ log(x+\\lambda_2) & \\text{if} \\ \\lambda_1 = 0 \\end{cases}\n", "\$$" ] }, { "cell_type": "code", "collapsed": false, "input": [ "# Box-Cox transformed predictors\n", "trainX_trans = pd.read_csv(\"../datasets/solubility/solTrainXtrans.csv\").drop(\"Unnamed: 0\", axis=1)\n", "testX_trans = pd.read_csv(\"../datasets/solubility/solTestXtrans.csv\").drop(\"Unnamed: 0\", axis=1)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 64 }, { "cell_type": "heading", "level": 6, "metadata": {}, "source": [ "Q1: Is it safet to assume that the relationship between the predictors and outcome is linear?" ] }, { "cell_type": "code", "collapsed": false, "input": [ "trainX_trans_c = trainX_trans[trainX_trans.columns[-20:]] # 20 continuous predictors\n", "\n", "# lowess (local smoother)\n", "import statsmodels.api as sm\n", "lowess = sm.nonparametric.lowess" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 65 }, { "cell_type": "code", "collapsed": false, "input": [ "def plotContinuousPredictors(X, y, nrows=4, ncols=5):\n", " '''plot the continous predictors (default 20) versus the outcome'''\n", " fig, axarr = plt.subplots(nrows, ncols)\n", " fig.tight_layout()\n", " \n", " for r in range(nrows):\n", " for c in range(ncols):\n", " plotOnePredictor(axarr[r, c], X.iloc[:, (r+1)*(c+1)-1], y)\n", " \n", "def plotOnePredictor(ax, X, y):\n", " '''plot one predictor versus the outcome'''\n", " z = lowess(np.squeeze(y), np.squeeze(X), 0.88) # return sorted X and y_fit\n", " ax.scatter(X, y, alpha=0.4)\n", " ax.plot(z[:, 0], z[:, 1], 'r', linewidth=2)\n", " ax.set_title(X.name)\n", " \n", " \n", "plotContinuousPredictors(trainX_trans_c, trainY)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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zz8e0w2VEVwQ85cWFkGfz+ganRgiBHMVBFqfC0My5z7mmGTB0cz5g6MZgOBi6MRgOw9XN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n+CyZSOxVKGqmbi9dZiNm/g/fcr+Pd/f5SNG6++qORodXV16O3buRPy8ljrHzDrqc8+lkw2zWze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6UUACWoqq2zIoMK4eEXYLVmIO0E4DBhYWYaG4+ekfe5557j17/+GrgRp3M5kI5efz2qakBR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\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IIyw09EaIB09jRczh/mFcWwh1o9D06WP57LN9yKBN0k6fPrZbnLKyGuz20TQ0PAdAXFwi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\nhw4Zg7EJE2qprZ1Oc3MM4y7qR4Bexo4dZPbsv4n8+ryZoLhYGBw8H2M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"text": [ "" ] } ], "prompt_number": 66 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The smoothed regression lines indicate that there are some linear and non-linear relationship between the predictors and the outcome. Because of this, we might consider augmenting the predictor set with quadratic terms for some variables." ] }, { "cell_type": "heading", "level": 6, "metadata": {}, "source": [ "Q2: Are there significant between-predictor correlations?" ] }, { "cell_type": "code", "collapsed": false, "input": [ "# PCA scree plot\n", "from sklearn.decomposition import PCA\n", "from sklearn.preprocessing import scale\n", "\n", "# scale before PCA\n", "trainX_trans_scale = scale(trainX_trans)\n", "\n", "pca = PCA()\n", "pca.fit(trainX_trans_scale)\n", "\n", "# generate scree plot\n", "plt.plot(pca.explained_variance_ratio_)\n", "plt.xlim((-5, None))\n", "plt.ylim((-0.005, None))\n", "plt.xlabel('Percent of Total Variance')\n", "plt.ylabel('Component')" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 67, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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RcU1EnNvJfraaMQN23BHuvrtbnyhJkrRpHUvaImIm8BlgGbAPcGRE7D3qmEOB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\nQrfLLtUTIxYtqkbx5s9/6nr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"text": [ "" ] } ], "prompt_number": 67 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Notice that the amount of variability summarized by components drops sharply, with no one component accounting for more than 13% of the variance. This profile indicates that the structure of the data is contained in a much smaller number of dimensions than the number of dimensions of the original space; this is often due to a large number of collinearities among the predictors." ] }, { "cell_type": "code", "collapsed": false, "input": [ "# correlation matrix for continuous predictors\n", "corr_dataframe_c = trainX_trans_c.corr()\n", "\n", "# compute hierarchical cluster on both rows and columns for correlation matrix and plot heatmap \n", "def corr_heatmap(corr_dataframe):\n", " import scipy.cluster.hierarchy as sch\n", " \n", " corr_matrix = np.array(corr_dataframe)\n", " col_names = corr_dataframe.columns\n", " \n", " Y = sch.linkage(corr_matrix, 'single', 'correlation')\n", " Z = sch.dendrogram(Y, color_threshold=0, no_plot=True)['leaves']\n", " corr_matrix = corr_matrix[Z, :]\n", " corr_matrix = corr_matrix[:, Z]\n", " col_names = col_names[Z]\n", " im = plt.imshow(corr_matrix, interpolation='nearest', aspect='auto', cmap='bwr')\n", " plt.colorbar()\n", " plt.xticks(range(corr_matrix.shape[0]), col_names, rotation='vertical', fontsize=12)\n", " plt.yticks(range(corr_matrix.shape[0]), col_names[::-1], fontsize=12)\n", " \n", "# plot\n", "corr_heatmap(corr_dataframe_c)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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vxoyJo1sZMyaKLkAl0vYJlQkToujG/Bl5+uk42pVJtV8VDlCZPDmKbs3oZB7M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\nB/4OHNnuQDCnvT+hPORThBmKTYGtCbaHwimszOwOQ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"text": [ "" ] } ], "prompt_number": 68 }, { "cell_type": "markdown", "metadata": {}, "source": [ "There are many strong positive correlations (dard red). As discussed in Chapter 3, this could create problems in developing some models and appropriate pre-processing steps will need to be taken to account for this problem." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "6.2 Linear Regression" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The objective of ordinary least square is find the plane that minimize the sum-of-squared errors (SSE) between the observed and predicted response: $$\\text{SSE} = \\sum_{i=1}^n (y_i - \\hat{y}_i)^2,$$ where $y_i$ is the outcome and $\\hat{y}_i$ is the model prediction of that sample's outcome. Mathematically, the optimal plane can be shown to be $$\\hat{\\beta} = (\\pmb{X}^T \\pmb{X})^{-1} \\pmb{X}^T y,$$ where $\\pmb{X}$ is the matrix of predictors, $y$ is the response vector, and $\\hat{\\beta}$ is the parameter estimates for each predictor. Making some assumptions about the distribution of the residuals, it is straightforward to show these estimates minimize the bias component of the bias-variance trade-off." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Notice that a unique inverse of $\\pmb{X}^T \\pmb{X}$ exists when (1) no predictor can be determined from a combination of one or more of the other predictors and (2) the number of samples is greater than the number of predictors. Note that linear regression can still be used for prediction when collinearity exists within the data. But we lose the ability to meaningfully interpret the coefficients. In practice, highly correlated predictors might be managed manually by removing one of the offending predictors. However, if the number of predictors is large, this may be difficult. Also, on many occasions, relationships among predictors can be complex and involve many predictors. In these cases, manual removal of specific predictors may not be possible and models that can tolerate collinearity may be more useful.\n", "\n", "When condition (2) is true for a data set, we suggest using pre-processing techniques, such as removing pairwise correlated predictors and checking *variance inflation factor* (VIF). After pre-processing the data, if the number of predictors still outnumbers the number of observations, we need to consider PCA pre-processing, or simultaneous dimension reduction and regression via PLS or parameters shrinking estimates such as ridge regression, the lass or the elastic net." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Another drawback of multiple linear regression is that its solution is linear in the paramters. One visual clue to understanding if the relationship between predictors and the response is not linear is to examine the basic diagnostic plots. Curvature in the predicted-versus-residual plot is a primary indicator that the underlying relationship is not linear. Easily identifiable quadratic, cubic, or interactions between predictors can be accommodated in regression by add quadratic, cubic, and interactions of the original predictors." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A third notable problem with multiple linear regression is that it is prone to chasing observations that are away from the overall trend of the majority of the data. Observations that cause significant changes in the parameter estimates are called *influential*. One common approach to address these problems is to use an alternative metric to SSE that is less sensitive to large outliers, such as absolute errors and Huber function." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There are no tuning parameters for multiple linear regression. This fact, however, dose not impugn the practitioner from using rigorous model validation tools. In fact, we must use the same training and validation techniques to understand the predictive ability of this model on data which the model has not seen." ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Linear Regression for Solubility Data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Recall that we split the solubility data into training and test sets and applied a Box-Cox transformation to the continuous predictors in order to remove skewness. The next step is to identify predictors that have high pairwise correlations and to remove predictors so that no absolute pairwise correlation is greater than some pre-specified level.\n", "\n", "In this case, we remove predictors that have pairwise correlations greater than 0.9 using a heuristic approach introduced in Chapter 3." ] }, { "cell_type": "code", "collapsed": false, "input": [ "corr_dataframe = trainX_trans.corr()\n", "\n", "def remove_high_corr(corr_dataframe, thresh = 0.9):\n", " '''remove predictors with high pairwise correlation'''\n", " abs_corr = np.abs(corr_dataframe).as_matrix() # absolute correlation matrix\n", " col_names = list(corr_dataframe.columns)\n", " \n", " # set up diagonal to 0\n", " np.fill_diagonal(abs_corr, 0)\n", " \n", " print \"Removed predictors (in order): \\n\"\n", " while np.max(abs_corr) >= thresh:\n", " i, j = np.unravel_index(abs_corr.argmax(), abs_corr.shape) # find maximum element\n", " # print abs_corr[i, j]\n", " rdx = which_to_remove(i, j, abs_corr)\n", " # remove corresponding predictor\n", " print col_names.pop(rdx)\n", " abs_corr = np.delete(abs_corr, rdx, 0)\n", " abs_corr = np.delete(abs_corr, rdx, 1)\n", " \n", " return col_names\n", "\n", "def which_to_remove(i, j, abs_corr):\n", " '''compare two predictors and remove the one with higher abs correlation with other predictors'''\n", " i_absmean = np.mean(abs_corr[i, np.where(abs_corr[i,:] == 0)])\n", " j_absmean = np.mean(abs_corr[j, np.where(abs_corr[j,:] == 0)])\n", " \n", " return i if i_absmean > j_absmean else j\n", "\n", "# remained predictors\n", "col_remained = remove_high_corr(corr_dataframe)\n", "trainX_trans_filtered = trainX_trans[col_remained]\n", "testX_trans_filtered = testX_trans[col_remained]" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Removed predictors (in order): \n", "\n", "NumBonds\n", "NumSulfer\n", "FP203\n", "FP208\n", "NumNonHBonds\n", "NumChlorine\n", "NumHalogen\n", "FP183\n", "FP014\n", "FP194\n", "NumNitrogen\n", "NumAromaticBonds\n", "FP033\n", "FP166\n", "FP163\n", "FP180\n", "SurfaceArea2\n", "FP024\n", "FP175\n", "FP167\n", "FP141\n", "FP144\n", "FP155\n", "FP052\n", "FP056\n", "FP110\n", "NumCarbon\n", "FP005\n", "FP179\n", "FP136\n", "FP162\n", "FP087\n", "FP092\n", "FP112\n", "FP067\n", "FP051\n" ] } ], "prompt_number": 69 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Upon removing these predictors, a linear model was fit to the training data. The linear model was resampled using 10-fold cross-validation and the estimated RMSE and $\\text{R}^2$ is reported." ] }, { "cell_type": "code", "collapsed": false, "input": [ "from sklearn.linear_model import LinearRegression\n", "from sklearn.cross_validation import cross_val_score, ShuffleSplit\n", "\n", "cv = ShuffleSplit(trainX_trans_filtered.shape[0], n_iter=10, random_state=0)\n", "\n", "lm = LinearRegression()\n", "train_scores_mse = cross_val_score(lm, trainX_trans_filtered, trainY.values, cv=cv, \n", " scoring = 'mean_squared_error')\n", "train_scores_rmse = np.sqrt(-1.0 * train_scores_mse)\n", "\n", "train_scores_r2 = cross_val_score(lm, trainX_trans_filtered, trainY.values, cv=cv, \n", " scoring = 'r2')\n", "print \"CV estimated RMSE: {0} \\nCV estimated R2: {1}\".format(np.mean(train_scores_rmse), np.mean(train_scores_r2))" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "CV estimated RMSE: 0.707044315368 \n", "CV estimated R2: 0.874723530558\n" ] } ], "prompt_number": 70 }, { "cell_type": "code", "collapsed": false, "input": [ "# apply to the test set\n", "lm.fit(trainX_trans_filtered, trainY.values)\n", "testY_pred = lm.predict(testX_trans_filtered)\n", "\n", "from sklearn.metrics import r2_score, mean_squared_error\n", "test_score_r2 = r2_score(testY.values, testY_pred)\n", "test_score_rmse = np.sqrt(mean_squared_error(testY.values, testY_pred))\n", "\n", "print \"Test set RMSE: {0} \\nTest set R2: {1}\".format(test_score_rmse, test_score_r2)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Test set RMSE: 0.742917835704 \n", "Test set R2: 0.871834926473\n" ] } ], "prompt_number": 71 }, { "cell_type": "code", "collapsed": false, "input": [ "# regression diagnostic\n", "fig, (ax1, ax2) = plt.subplots(1, 2)\n", "\n", "ax1.scatter(testY_pred, testY.values)\n", "ax1.set(xlim=(-11, 2), ylim=(-11, 2))\n", "ax1.plot(ax1.get_xlim(), ax1.get_ylim(), ls=\"--\", c=\".3\", linewidth=2)\n", "ax1.set_xlabel(\"Predicted\")\n", "ax1.set_ylabel(\"Observed\")\n", "\n", "ax2.scatter(testY_pred, testY.values-testY_pred)\n", "ax2.set(xlim=(-11, 2))\n", "ax2.plot(ax1.get_xlim(), (0, 0), ls=\"--\", c=\".3\", linewidth=2)\n", "ax2.set_xlabel(\"Predicted\")\n", "ax2.set_ylabel(\"Residual\")" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 72, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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jDBgwkA8/3BV3zUhgP9ExZjoLDHuI9w7OnDlXZq6CIBgS79nq6oK2trXArIw8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"text": [ "" ] } ], "prompt_number": 72 }, { "cell_type": "markdown", "metadata": {}, "source": [ "There does not appear to be any bias in the prediction, and the distribution between the predicted values and residuals appears to be random about zero." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "6.3 Partial Least Squares" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If the correlation among predictors is high, then the ordinary least squares solution for multiple linear regression will have high variability and will become unstable. One the other hand, if the number of predictors may be greater than the number of observations, ordinary least squares in its usual form will be unable to find a unique set of regression coefficients that minimize the SSE.\n", "\n", "A couple of common solutions include pre-processing the predictor by either (1) removal of the highly correlated predictors or (2) conducting PCA on the predictors. Removing highly correlated predictors ensures that pairwise correlations among predictors are below a pre-specified threshold. However, this process does not necessarily ensure that linear combinations of predictors are uncorrelated with each other, i.e., it may not guarantee a stable least squares solution. Alternatively, using PCA for pre-processing guarantees that the resulting predictors, or combinations thereof, will be uncorrelated. The trade-off in using PCA is that the new predictors are linear combinations of the original predictors, and thus, the practical understanding of the new predictors can become murky." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Pre-processing predictors via PCA prior to performing regression is known as principal component regression (PCR). While this two-step regression approach (dimension reduction, then regression) has been widely applied to problems with inherently highly correlated predictors or problems with more predictors than observations, it can easily be misled. Specifically, dimension reduction via PCA does not necessarily produce new predictors that explain the response, since PCA does not consider any aspects of teh response when it selects its components. Instead, it simply chases the variability present throughout the predictor space. Because of this inherent problem with PCR, we recommend using PLS when there are correlated predictors and a linear regression-type solution is desired." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "PLS find linear combinations of the predictors just like PCA. While the PCA linear combinations are chosen to maximally summarize predictor space variability, the PLS linear combinations of predictors are chosen to maximally summarize covariance with the response. This means that PLS finds components that maximally summarize the variation of the predictors while simultaneously requiring these components to have maximum correlation with the response. It strikes a compromise between the objectives of predictor space dimension reduction and a predictive relationship with the reponse. In other words, PLS is a *supervised* dimension reduction procedure; PCR is an *unsupervised* procedure." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Prior to performing PLS, the predictors should be centered and scaled, especially if the predictors are on scale of differing magnitude. The PLS has one tuning parameter: the number of components to retain. Resampling techniques can be used to determine the optimal number of components." ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "PCR and PLSR for Solubility Data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Return to our previous example, 10-fold cross-validation was used to determine the optimal number of components to retain that minimize RMSE in both PCR and PLSR." ] }, { "cell_type": "code", "collapsed": false, "input": [ "# RMSEs for 50 components were examined\n", "pcr_rmse = np.zeros([50, 2])\n", "plsr_rmse = np.zeros([50, 2])\n", "\n", "# 10-fold CV\n", "cv = ShuffleSplit(trainX_trans.shape[0], n_iter=10)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 73 }, { "cell_type": "code", "collapsed": false, "input": [ "def optimal_with_osr(rmse):\n", " '''Return the minimum RMSE and its # of components using \"one-standard error\" rule'''\n", " n_best = np.argmin(rmse[:, 0])\n", " rmse_min = rmse[n_best, 0] + rmse[n_best, 1]\n", " n_best = np.min(np.where(rmse[:, 0] <= rmse_min))\n", " return (n_best+1), rmse_min" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 74 }, { "cell_type": "code", "collapsed": false, "input": [ "# PCR\n", "from sklearn.decomposition import PCA\n", "\n", "for n_compo in range(len(pcr_rmse)):\n", " pca = PCA(n_components= n_compo+1)\n", " pca_compo = pca.fit_transform(trainX_trans_scale)\n", " train_scores_mse = cross_val_score(LinearRegression(), pca_compo, trainY.values, cv=cv, scoring = 'mean_squared_error')\n", " pcr_rmse[n_compo, 0] = np.mean(np.sqrt(-1.0 * train_scores_mse))\n", " pcr_rmse[n_compo, 1] = np.std(np.sqrt(-1.0 * train_scores_mse))\n", "\n", "n_best, rmse_min = optimal_with_osr(pcr_rmse)\n", "print \"With one-standard error rule, the minimum PCR RMSE is {0} with {1} components\".format(rmse_min, n_best)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "With one-standard error rule, the minimum PCR RMSE is 0.860014338691 with 43 components\n" ] } ], "prompt_number": 75 }, { "cell_type": "code", "collapsed": false, "input": [ "# PLSR\n", "from sklearn.cross_decomposition import PLSRegression\n", "\n", "for n_compo in range(len(plsr_rmse)):\n", " plsr= PLSRegression(n_components= n_compo+1, scale=False)\n", " train_scores_mse = cross_val_score(plsr, trainX_trans_scale, trainY.values, cv=cv, scoring = 'mean_squared_error')\n", " plsr_rmse[n_compo, 0] = np.mean(np.sqrt(-1.0 * train_scores_mse))\n", " plsr_rmse[n_compo, 1] = np.std(np.sqrt(-1.0 * train_scores_mse))\n", "\n", "n_best, rmse_min = optimal_with_osr(plsr_rmse)\n", "print \"With one-standard error rule, the minimum PLSR RMSE is {0} with {1} components\".format(rmse_min, n_best)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "With one-standard error rule, the minimum PLSR RMSE is 0.726648755663 with 12 components\n" ] } ], "prompt_number": 76 }, { "cell_type": "code", "collapsed": false, "input": [ "plt_pcr, = plt.plot(pcr_rmse[:,0], '-x')\n", "plt_plsr, = plt.plot(plsr_rmse[:,0], '-o')\n", "plt.xlim((-1, None))\n", "plt.xlabel(\"# Components\")\n", "plt.ylabel(\"RMSE (Cross-Validation)\")\n", "plt.legend([plt_pcr, plt_plsr], ['PCR', 'PLSR'])" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 77, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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2YJmqXz8YMcLrKERERCRVIlln7ENgkLV2ZdlxRyDfWrt3CuIrjyEjesYAtm51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\n2h6FuavnIouzUI7KYcKQCTb7WZTjR4jim7t6rsaxAwAJzRM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"text": [ "" ] } ], "prompt_number": 77 }, { "cell_type": "markdown", "metadata": {}, "source": [ "With these data, we see the supervised dimension reduction finds a minimum RMSE with significantly fewer components than unsupervised dimension reduction." ] }, { "cell_type": "code", "collapsed": false, "input": [ "from scipy.stats import pearsonr\n", "\n", "# compoare the first two components\n", "pca2 = PCA(n_components=2)\n", "pca2.fit(trainX_trans_scale)\n", "\n", "plsr2 = PLSRegression(n_components=2, scale=False)\n", "plsr2.fit(trainX_trans_scale, trainY.values)\n", "\n", "# visulization\n", "fig, axarr = plt.subplots(2, 2, sharex=True, sharey=True)\n", "#fig.tight_layout()\n", "\n", "axarr[0,0].scatter(pca2.transform(trainX_trans_scale)[:, 0], trainY.values)\n", "axarr[0,0].set_title(\"PCA Component 1\")\n", "corr = pearsonr(pca2.transform(trainX_trans_scale)[:, 0], trainY.values[:,0])[0]\n", "axarr[0,0].text(10, -12, 'corr:' + str(round(corr, 2)))\n", "\n", "axarr[0,1].scatter(pca2.transform(trainX_trans_scale)[:, 1], trainY.values)\n", "axarr[0,1].set_title(\"PCA Component 2\")\n", "corr = pearsonr(pca2.transform(trainX_trans_scale)[:, 1], trainY.values[:,0])[0]\n", "axarr[0,1].text(10, -12, 'corr:' + str(round(corr, 2)))\n", "\n", "axarr[1,0].scatter(plsr2.transform(trainX_trans_scale)[:, 0], trainY.values)\n", "axarr[1,0].set_title(\"PLS Component 1\")\n", "corr = pearsonr(plsr2.transform(trainX_trans_scale)[:, 0], trainY.values[:,0])[0]\n", "axarr[1,0].text(10, -12, 'corr:' + str(round(corr, 2)))\n", "\n", "axarr[1,1].scatter(plsr2.transform(trainX_trans_scale)[:, 1], trainY.values)\n", "axarr[1,1].set_title(\"PLS Component 2\")\n", "corr = pearsonr(plsr2.transform(trainX_trans_scale)[:, 0], trainY.values[:,0])[0]\n", "axarr[1,1].text(10, -12, 'corr:' + str(round(corr, 2)))\n", "\n", "fig.text(0.5, 0.06, 'Component Score', ha='center', va='center')\n", "fig.text(0.06, 0.5, 'Solubility', va='center', rotation='vertical')" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 78, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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buc6TuAu1t7dXF/41Sm9zpHxSJdysJyq8AFclBFiNfvzxZmQVE+DCGBHbotUk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\nP+p5aSytEa30hFyMQs0JXGfFTGKTSYIXiADGvIj1X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"text": [ "" ] } ], "prompt_number": 78 }, { "cell_type": "markdown", "metadata": {}, "source": [ "It is not surprising that the correlation between these components and the response is greater for PLS than PCR." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Prediction of the test set using the optimal PCR and PLS models is compared." ] }, { "cell_type": "code", "collapsed": false, "input": [ "from sklearn.preprocessing import scale\n", "testX_trans_scale = scale(testX_trans)\n", "\n", "# PCR\n", "pca = PCA(n_components=34) # optimal\n", "pca.fit(trainX_trans_scale)\n", "trainX_pca = pca.transform(trainX_trans_scale)\n", "testX_pca = pca.transform(testX_trans_scale)\n", "lm = LinearRegression()\n", "lm.fit(trainX_pca, trainY.values)\n", "testY_pca_pred = lm.predict(testX_pca)\n", "\n", "# PLSR\n", "plsr = PLSRegression(n_components=7, scale=False)\n", "plsr.fit(trainX_trans_scale, trainY.values)\n", "testY_plsr_pred = plsr.predict(testX_trans_scale)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 79 }, { "cell_type": "code", "collapsed": false, "input": [ "# regression diagnostic\n", "fig, axarr = plt.subplots(2, 2)\n", "\n", "axarr[0, 0].scatter(testY_pca_pred, testY)\n", "axarr[0, 0].set(xlim=(-11, 2), ylim=(-11, 2))\n", "axarr[0, 0].plot(axarr[0,0].get_xlim(), axarr[0,0].get_ylim(), ls=\"--\", c=\".3\", linewidth=2)\n", "axarr[0, 0].set_xlabel(\"Predicted\")\n", "axarr[0, 0].set_ylabel(\"Observed\")\n", "\n", "axarr[0, 1].scatter(testY_pca_pred, testY-testY_pca_pred)\n", "axarr[0, 1].set(xlim=(-11, 2))\n", "axarr[0, 1].plot(axarr[0,1].get_xlim(), (0,0), ls=\"--\", c=\".3\", linewidth=2)\n", "axarr[0, 1].set_xlabel(\"Predicted\")\n", "axarr[0, 1].set_ylabel(\"Residual\")\n", "\n", "axarr[1, 0].scatter(testY_plsr_pred, testY)\n", "axarr[1, 0].set(xlim=(-11, 2), ylim=(-11, 2))\n", "axarr[1, 0].plot(axarr[0,0].get_xlim(), axarr[1,0].get_ylim(), ls=\"--\", c=\".3\", linewidth=2)\n", "axarr[1, 0].set_xlabel(\"Predicted\")\n", "axarr[1, 0].set_ylabel(\"Observed\")\n", "\n", "axarr[1, 1].scatter(testY_plsr_pred, testY-testY_plsr_pred)\n", "axarr[1, 1].set(xlim=(-11, 2))\n", "axarr[1, 1].plot(axarr[1,1].get_xlim(), (0,0), ls=\"--\", c=\".3\", linewidth=2)\n", "axarr[1, 1].set_xlabel(\"Predicted\")\n", "axarr[1, 1].set_ylabel(\"Residual\")" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 80, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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0tNE8JhRqMnIl5k9f281ulJrvoBv9VXTFlM2mlNnQJhPFkK0yTq4jHDfNaE5Z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\nSQHJCV9T4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"text": [ "" ] } ], "prompt_number": 80 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The predictive ability of each method is good, and the residuals appear to be randomly scattered about zero. Although the predictive ability of these models is close, PLS finds a simpler model that uses far fewer components than PCR." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "6.4 Penalized Models" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Under standard assumptions, the coefficients produced by ordinary least squares regression are unbiased and, of all unbiased linear techniques, this model also has the lowest variance. However, given that the MSE is a combination of variane and bias, it is very possible to produce models with smaller MSEs by allowing the parameter estimates to be biased. Combatting collinearity by using biased models may result in regression models where the overall MSE is competitive.\n", "\n", "One method of creating biased regression models is to add a penalty to the sum of the squared errors. Recall that original least squares regression found parameter estimates to minimize the sum of the squared errors: $$\\text{SSE} = \\sum_{i=1}^n (y_i - \\hat{y}_i)^2.$$ When the model over-fits the data, or when there are issues with collinearity, the linear regression parameter estimates may become inflated. Controlling (or *regularizing*) the parameter estimates can be accomplished by adding a penalty to the SSE if the estimates become large." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "*Ridge regression* adds a second-order penalty on the SSE: $$\\text{SSE}_{L_2} = \\sum_{i=1}^n (y_i - \\hat{y}_i)^2 + \\lambda \\sum_{j=1}^P \\beta_j^2.$$ In effect, this method *shrinks* the estimates towards 0 as the $\\lambda$ penalty become large.\n", "\n", "By adding the penalty, we are making a trade-off between the model variance and bias. By sacrificing some bias, we can often reduce the variance enough to make the overall MSE lower than unbiased models." ] }, { "cell_type": "code", "collapsed": false, "input": [ "# path of the ridge regression coefficients\n", "from sklearn.linear_model import Ridge\n", "\n", "lambda_range = np.linspace(0.0, 0.01, 600)\n", "ridgeModel = Ridge(normalize=True)\n", "coeff_path = []\n", "\n", "for a in lambda_range:\n", " ridgeModel.set_params(alpha = a)\n", " ridgeModel.fit(trainX_trans, trainY)\n", " coeff_path.append(ridgeModel.coef_[0])\n", "\n", "ax = plt.gca()\n", "ax.plot(lambda_range, coeff_path)\n", "ax.set_xlim((-0.0005, 0.0105))\n", "plt.xlabel(\"Penalty\")\n", "plt.ylabel(\"Standardized Coefficient\")" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 81, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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5LH/5cvwDPn/+wtlcctKzeNUHfsrHPw7nvqCTX73nF0y/85d8stvjqXdt4J+e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"text": [ "" ] } ], "prompt_number": 81 }, { "cell_type": "markdown", "metadata": {}, "source": [ "When there is no penalty, many parameters have reasonable values, but some parameter estimates are abnormally large. These large values are indicative of collinearity issues. As the penalty is increased, the paramter estimates move closer to 0 at diferent rate." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Use cross-validation, the penalty value was optimized (over-fit -> under-fit)." ] }, { "cell_type": "code", "collapsed": false, "input": [ "# penalty value versus RMSE\n", "lambda_range = np.linspace(0.0, 0.1, 15)\n", "score_rmse = np.zeros(15)\n", "\n", "ridgeModel = Ridge(normalize=True)\n", "\n", "for adx, a in enumerate(lambda_range):\n", " temp_scores = cross_val_score(ridgeModel.set_params(alpha = a),\n", " trainX_trans, trainY.values,\n", " cv=10, scoring=\"mean_squared_error\")\n", " temp_scores = np.sqrt(-1.0 * temp_scores)\n", " score_rmse[adx] = np.mean(temp_scores)\n", " \n", "plt.plot(lambda_range, score_rmse, '-o')\n", "plt.xlabel(\"Penalty\")\n", "plt.ylabel(\"RMSE (Cross-Validation)\")\n", "plt.xlim((-0.005, 0.105))" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 82, "text": [ "(-0.005, 0.105)" ] }, { "metadata": {}, "output_type": "display_data", "png": 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i7bcfHHts8VxFa6g1PWpPA9cAI4GD3X2Bmb3s7rvkI8D2KvQeNYBNNkn+Sth8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\n4kTNzMzMrKD8jJqZmZlZzvyMmpmZmVmLcaKWQd7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"text": [ "" ] } ], "prompt_number": 82 }, { "cell_type": "markdown", "metadata": {}, "source": [ "While ridge regression shrinks the parameter estimates towards 0, the model does not set the values to absolute 0 for any value of the penalty. Even though some parameter estimates become negligibly small, this model does not conduct *feature selection*." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A popular alternative to ridge regression is the *least absolute shrinkage and selection operator* model, known as the *lasso*. It uses a similar penalty to ridge regression $$\\text{SSE}_{L_1} = \\sum_{i=1}^n (y_i - \\hat{y}_i)^2 + \\lambda \\sum_{j=1}^P |\\beta_j|.$$ While this may seem like a small modification, the practical implications are significant. While the regression coefficients are still shrunk towards 0, a consequence of penalizing the absolute values is that some parametes are actually set to 0 for some values of $\\lambda$. Thus the lasso yields models that simultaneously use regularization to improve the model and to conduct feature selection." ] }, { "cell_type": "code", "collapsed": false, "input": [ "# path of the lasso regression coefficients\n", "from sklearn.linear_model import lars_path\n", "\n", "# compute regularization path using the LARS\n", "lambdas, _, coefs = lars_path(trainX_trans.values, trainY.values[:,0], method = 'lasso', verbose=True)\n", "\n", "xx = np.sum(np.abs(coefs.T), axis=1)\n", "xx /= xx[-1]\n", "\n", "plt.plot(xx, coefs.T)\n", "plt.xlabel('Fraction of Full Solution')\n", "plt.ylabel('Standardized Coefficient')" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "." ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 83, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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An8kePtVdN/JWMlbcVPdQvHJ953kea9eu5b333mveli9fzvLly3Fdl3HjxjFu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\nrNovIxFZQX7/8o8EY0IIkc/OPx9eegn+8Ae4+GJobfW7RkLkH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"text": [ "" ] } ], "prompt_number": 83 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The x-axis is the fraction of the full solution (i.e., ordinary least squares with no penalty). Smaller values on the x-axis indicate that a large penalty has been used. When the penalty is large, many of the regression coefficients are set to 0.\n", "\n", "A significant advancement for this model, the least angle regression (LARS), is a broad framework that encompassess the lasso and similar models. The LARS model can be used to fit lasso models more efficiently, especially in high-dimensional problems." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A generalization of the lasso model is the *elastic net*. The model combines te two types of penalties: $$\\text{SSE}_{Enet} = \\sum_{i=1}^n (y_i - \\hat{y}_i)^2 + \\lambda_1 \\sum_{j=1}^P |\\beta_j| + \\lambda_2 \\sum_{j=1}^P \\beta_j^2.$$ The advantage of this model is that it enables effective regularization via the ridge-type penalty with the feature selection quality of the lasso penalty. Both the penalties require tuning to achieve optimal performance." ] } ], "metadata": {} } ] }