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David Monllaó c1b1a5d6ac Support for multiple training datasets (#38 )

* Multiple training data sets allowed

* Tests with multiple training data sets

* Updating docs according to #38

Documenting all models which predictions will be based on all
training data provided.

Some models already supported multiple training data sets.

2017-02-01 19:06:38 +01:00

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LeastSquares Linear Regression

Linear model that use least squares method to approximate solution.

Train

To train a model simply provide train samples and targets values (as array). Example:

$samples = [[60], [61], [62], [63], [65]];
$targets = [3.1, 3.6, 3.8, 4, 4.1];

$regression = new LeastSquares();
$regression->train($samples, $targets);

You can train the model using multiple data sets, predictions will be based on all the training data.

Predict

To predict sample target value use predict method with sample to check (as array). Example:

$regression->predict([64]);
// return 4.06

Multiple Linear Regression

The term multiple attached to linear regression means that there are two or more sample parameters used to predict target. For example you can use: mileage and production year to predict price of a car.

$samples = [[73676, 1996], [77006, 1998], [10565, 2000], [146088, 1995], [15000, 2001], [65940, 2000], [9300, 2000], [93739, 1996], [153260, 1994], [17764, 2002], [57000, 1998], [15000, 2000]];
$targets = [2000, 2750, 15500, 960, 4400, 8800, 7100, 2550, 1025, 5900, 4600, 4400];

$regression = new LeastSquares();
$regression->train($samples, $targets);
$regression->predict([60000, 1996])
// return 4094.82

Intercept and Coefficients

After you train your model you can get the intercept and coefficients array.

$regression->getIntercept();
// return -7.9635135135131

$regression->getCoefficients();
// return [array(1) {[0]=>float(0.18783783783783)}]

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