@@ -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\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 |
@@ -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\DecisionTree; |
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\Classification\Linear; |
6 | 6 | |
@@ -193,7 +193,7 @@ discard block |
||
193 | 193 | * The gradient of the cost function to be used with gradient descent: |
194 | 194 | * ∇J(x) = -(y - h(x)) = (h(x) - y) |
195 | 195 | */ |
196 | - $callback = function ($weights, $sample, $y) use ($penalty) { |
|
196 | + $callback = function($weights, $sample, $y) use ($penalty) { |
|
197 | 197 | $this->weights = $weights; |
198 | 198 | $hX = $this->output($sample); |
199 | 199 | |
@@ -224,7 +224,7 @@ discard block |
||
224 | 224 | * The gradient of the cost function: |
225 | 225 | * ∇J(x) = -(h(x) - y) . h(x) . (1 - h(x)) |
226 | 226 | */ |
227 | - $callback = function ($weights, $sample, $y) use ($penalty) { |
|
227 | + $callback = function($weights, $sample, $y) use ($penalty) { |
|
228 | 228 | $this->weights = $weights; |
229 | 229 | $hX = $this->output($sample); |
230 | 230 |
@@ -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\Linear; |
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\Classification\Linear; |
6 | 6 | |
@@ -170,7 +170,7 @@ discard block |
||
170 | 170 | protected function runTraining(array $samples, array $targets) |
171 | 171 | { |
172 | 172 | // The cost function is the sum of squares |
173 | - $callback = function ($weights, $sample, $target) { |
|
173 | + $callback = function($weights, $sample, $target) { |
|
174 | 174 | $this->weights = $weights; |
175 | 175 | |
176 | 176 | $prediction = $this->outputClass($sample); |
@@ -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\Linear; |
6 | 6 | |
@@ -64,7 +64,7 @@ discard block |
||
64 | 64 | protected function runTraining(array $samples, array $targets) |
65 | 65 | { |
66 | 66 | // The cost function is the sum of squares |
67 | - $callback = function ($weights, $sample, $target) { |
|
67 | + $callback = function($weights, $sample, $target) { |
|
68 | 68 | $this->weights = $weights; |
69 | 69 | |
70 | 70 | $output = $this->output($sample); |