|
B
|
MeanScaleNormalization::prepareNormalizationData()
|
6
|
10
|
7
|
7
|
1
|
1
|
0
|
|
B
|
Algorithm\GradientDescendent::train()
|
0
|
19
|
4
|
4
|
2
|
1
|
0
|
|
B
|
MeanScaleNormalization::calculateCoefficient()
|
0
|
22
|
3
|
3
|
2
|
1
|
0
|
|
A
|
Algorithm\GradientDescendent::doStep()
|
0
|
12
|
4
|
4
|
1
|
1
|
0
|
|
A
|
LinearRegressionService::train()
|
0
|
15
|
1
|
?
|
1
|
0
|
0
|
|
A
|
GradientDescendent::calculateStepCost()
|
0
|
16
|
2
|
2
|
1
|
1
|
0
|
|
A
|
Domain\Hypothesis\Linear::calculate()
|
0
|
6
|
2
|
2.02
|
1
|
0
|
0
|
|
A
|
MachineLearning\Domain\Model\Dataset::current()
|
0
|
3
|
1
|
1
|
1
|
0
|
0
|
|
A
|
Domain\Hypothesis\Linear::derivative()
|
0
|
5
|
2
|
2.03
|
1
|
0
|
0
|
|
A
|
Domain\Model\Training::__construct()
|
0
|
13
|
1
|
?
|
1
|
0
|
0
|
|
A
|
Hypothesis\Linear::createResultFromData()
|
0
|
4
|
1
|
1
|
1
|
0
|
0
|
|
A
|
Domain\Model\Result::__construct()
|
0
|
3
|
1
|
1
|
1
|
0
|
0
|
|
A
|
Hypothesis\Linear::getParameters()
|
0
|
6
|
1
|
1
|
1
|
0
|
0
|
|
A
|
Domain\Model\Training::predict()
|
0
|
3
|
1
|
?
|
1
|
0
|
1
|
|
A
|
MeanScaleNormalization::normalizeValue()
|
0
|
9
|
2
|
2
|
2
|
1
|
0
|
zeopix /
MachineLearning
