@@ -1,6 +1,6 @@ |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\NeuralNetwork\ActivationFunction; |
6 | 6 |
@@ -1,6 +1,6 @@ |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\Classification; |
6 | 6 |
@@ -1,6 +1,6 @@ |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\FeatureExtraction\StopWords; |
6 | 6 |
@@ -1,6 +1,6 @@ discard block |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\Helper\Optimizer; |
6 | 6 | |
@@ -240,7 +240,7 @@ discard block |
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240 | 240 | { |
241 | 241 | // Check for early stop: No change larger than threshold (default 1e-5) |
242 | 242 | $diff = array_map( |
243 | - function ($w1, $w2) { |
|
243 | + function($w1, $w2) { |
|
244 | 244 | return abs($w1 - $w2) > $this->threshold ? 1 : 0; |
245 | 245 | }, |
246 | 246 | $oldTheta, |
@@ -1,6 +1,6 @@ |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\Helper\Optimizer; |
6 | 6 |
@@ -1,6 +1,6 @@ discard block |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\Clustering; |
6 | 6 | |
@@ -101,7 +101,7 @@ discard block |
||
101 | 101 | $total += $val; |
102 | 102 | } |
103 | 103 | |
104 | - $this->membership[] = array_map(function ($val) use ($total) { |
|
104 | + $this->membership[] = array_map(function($val) use ($total) { |
|
105 | 105 | return $val / $total; |
106 | 106 | }, $row); |
107 | 107 | } |
@@ -1,6 +1,6 @@ discard block |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\Classification; |
6 | 6 | |
@@ -101,7 +101,7 @@ discard block |
||
101 | 101 | $this->dataType[$label][$i] = self::NOMINAL; |
102 | 102 | $this->discreteProb[$label][$i] = array_count_values($values); |
103 | 103 | $db = &$this->discreteProb[$label][$i]; |
104 | - $db = array_map(function ($el) use ($numValues) { |
|
104 | + $db = array_map(function($el) use ($numValues) { |
|
105 | 105 | return $el / $numValues; |
106 | 106 | }, $db); |
107 | 107 | } else { |
@@ -132,7 +132,7 @@ discard block |
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132 | 132 | |
133 | 133 | return $this->discreteProb[$label][$feature][$value]; |
134 | 134 | } |
135 | - $std = $this->std[$label][$feature] ; |
|
135 | + $std = $this->std[$label][$feature]; |
|
136 | 136 | $mean = $this->mean[$label][$feature]; |
137 | 137 | // Calculate the probability density by use of normal/Gaussian distribution |
138 | 138 | // Ref: https://en.wikipedia.org/wiki/Normal_distribution |
@@ -1,6 +1,6 @@ |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\Classification\Ensemble; |
6 | 6 |
@@ -1,6 +1,6 @@ |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\Classification\Ensemble; |
6 | 6 |