Changeset 10536:1d480a8785c6 in orange for docs/reference/rst/Orange.regression.lasso.rst
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 03/15/12 17:13:46 (2 years ago)
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docs/reference/rst/Orange.regression.lasso.rst
r9372 r10536 1 ############################ 2 Lasso regression (``lasso``) 3 ############################ 4 1 5 .. automodule:: Orange.regression.lasso 6 7 .. index:: regression 8 9 .. _`Lasso regression. Regression shrinkage and selection via the lasso`: 10 http://wwwstat.stanford.edu/~tibs/lasso/lasso.pdf 11 12 13 `The Lasso <http://wwwstat.stanford.edu/~tibs/lasso/lasso.pdf>`_ is a shrinkage 14 and selection method for linear regression. It minimizes the usual sum of squared 15 errors, with a bound on the sum of the absolute values of the coefficients. 16 17 To fit the regression parameters on housing data set use the following code: 18 19 .. literalinclude:: code/lassoexample.py 20 :lines: 9,10,11 21 22 .. autoclass:: LassoRegressionLearner 23 :members: 24 25 .. autoclass:: LassoRegression 26 :members: 27 28 29 .. autoclass:: LassoRegressionLearner 30 :members: 31 32 .. autoclass:: LassoRegression 33 :members: 34 35 Utility functions 36  37 38 .. autofunction:: center 39 40 .. autofunction:: get_bootstrap_sample 41 42 .. autofunction:: permute_responses 43 44 45 ======== 46 Examples 47 ======== 48 49 To predict values of the response for the first five instances 50 use the code 51 52 .. literalinclude:: code/lassoexample.py 53 :lines: 14,15 54 55 Output 56 57 :: 58 59 Actual: 24.00, predicted: 24.58 60 Actual: 21.60, predicted: 23.30 61 Actual: 34.70, predicted: 24.98 62 Actual: 33.40, predicted: 24.78 63 Actual: 36.20, predicted: 24.66 64 65 To see the fitted regression coefficients, print the model 66 67 .. literalinclude:: code/lassoexample.py 68 :lines: 17 69 70 The output 71 72 :: 73 74 Variable Coeff Est Std Error p 75 Intercept 22.533 76 CRIM 0.000 0.023 0.480 77 INDUS 0.010 0.023 0.300 78 RM 1.303 0.994 0.000 *** 79 AGE 0.002 0.000 0.320 80 PTRATIO 0.191 0.209 0.050 . 81 LSTAT 0.126 0.105 0.000 *** 82 Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 empty 1 83 84 85 For 7 variables the regression coefficient equals 0: 86 ZN 87 CHAS 88 NOX 89 DIS 90 RAD 91 TAX 92 B 93 94 shows that some of the regression coefficients are equal to 0. 95
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