@@ -18,7 +18,7 @@ |
||
| 18 | 18 | throw new InvalidArgumentException('Size of given arrays does not match'); |
| 19 | 19 | } |
| 20 | 20 | |
| 21 | - return array_sum(array_map(function ($m, $n) { |
|
| 21 | + return array_sum(array_map(function($m, $n) { |
|
| 22 | 22 | return abs($m - $n); |
| 23 | 23 | }, $a, $b)); |
| 24 | 24 | } |
@@ -51,7 +51,7 @@ |
||
| 51 | 51 | $mean = Mean::arithmetic($numbers); |
| 52 | 52 | |
| 53 | 53 | return array_sum(array_map( |
| 54 | - function ($val) use ($mean) { |
|
| 54 | + function($val) use ($mean) { |
|
| 55 | 55 | return ($val - $mean) ** 2; |
| 56 | 56 | }, |
| 57 | 57 | $numbers |
@@ -28,7 +28,7 @@ discard block |
||
| 28 | 28 | throw new InvalidArgumentException('The array must have at least 2 elements'); |
| 29 | 29 | } |
| 30 | 30 | |
| 31 | - $samplesPerClass = array_map(function (array $class): int { |
|
| 31 | + $samplesPerClass = array_map(function(array $class): int { |
|
| 32 | 32 | return count($class); |
| 33 | 33 | }, $samples); |
| 34 | 34 | $allSamples = array_sum($samplesPerClass); |
@@ -41,10 +41,10 @@ discard block |
||
| 41 | 41 | $dfbn = $classes - 1; |
| 42 | 42 | $dfwn = $allSamples - $classes; |
| 43 | 43 | |
| 44 | - $msb = array_map(function ($s) use ($dfbn) { |
|
| 44 | + $msb = array_map(function($s) use ($dfbn) { |
|
| 45 | 45 | return $s / $dfbn; |
| 46 | 46 | }, $ssbn); |
| 47 | - $msw = array_map(function ($s) use ($dfwn) { |
|
| 47 | + $msw = array_map(function($s) use ($dfwn) { |
|
| 48 | 48 | return $s / $dfwn; |
| 49 | 49 | }, $sswn); |
| 50 | 50 | |
@@ -72,7 +72,7 @@ discard block |
||
| 72 | 72 | |
| 73 | 73 | private static function sumOfFeaturesPerClass(array $samples): array |
| 74 | 74 | { |
| 75 | - return array_map(function (array $class) { |
|
| 75 | + return array_map(function(array $class) { |
|
| 76 | 76 | $sum = array_fill(0, count($class[0]), 0); |
| 77 | 77 | foreach ($class as $sample) { |
| 78 | 78 | foreach ($sample as $index => $feature) { |
@@ -93,7 +93,7 @@ discard block |
||
| 93 | 93 | } |
| 94 | 94 | } |
| 95 | 95 | |
| 96 | - return array_map(function ($sum) { |
|
| 96 | + return array_map(function($sum) { |
|
| 97 | 97 | return $sum ** 2; |
| 98 | 98 | }, $squares); |
| 99 | 99 | } |
@@ -126,7 +126,7 @@ |
||
| 126 | 126 | public function transpose(): self |
| 127 | 127 | { |
| 128 | 128 | if ($this->rows == 1) { |
| 129 | - $matrix = array_map(function ($el) { |
|
| 129 | + $matrix = array_map(function($el) { |
|
| 130 | 130 | return [$el]; |
| 131 | 131 | }, $this->matrix[0]); |
| 132 | 132 | } else { |
@@ -103,11 +103,11 @@ discard block |
||
| 103 | 103 | */ |
| 104 | 104 | protected function predictSample(array $sample): array |
| 105 | 105 | { |
| 106 | - $predicts = array_values(array_filter($this->getRules(), function ($rule) use ($sample) { |
|
| 106 | + $predicts = array_values(array_filter($this->getRules(), function($rule) use ($sample) { |
|
| 107 | 107 | return $this->equals($rule[self::ARRAY_KEY_ANTECEDENT], $sample); |
| 108 | 108 | })); |
| 109 | 109 | |
| 110 | - return array_map(function ($rule) { |
|
| 110 | + return array_map(function($rule) { |
|
| 111 | 111 | return $rule[self::ARRAY_KEY_CONSEQUENT]; |
| 112 | 112 | }, $predicts); |
| 113 | 113 | } |
@@ -176,7 +176,7 @@ discard block |
||
| 176 | 176 | $cardinality = count($sample); |
| 177 | 177 | $antecedents = $this->powerSet($sample); |
| 178 | 178 | |
| 179 | - return array_filter($antecedents, function ($antecedent) use ($cardinality) { |
|
| 179 | + return array_filter($antecedents, function($antecedent) use ($cardinality) { |
|
| 180 | 180 | return (count($antecedent) != $cardinality) && ($antecedent != []); |
| 181 | 181 | }); |
| 182 | 182 | } |
@@ -198,7 +198,7 @@ discard block |
||
| 198 | 198 | } |
| 199 | 199 | } |
| 200 | 200 | |
| 201 | - return array_map(function ($entry) { |
|
| 201 | + return array_map(function($entry) { |
|
| 202 | 202 | return [$entry]; |
| 203 | 203 | }, $items); |
| 204 | 204 | } |
@@ -212,7 +212,7 @@ discard block |
||
| 212 | 212 | */ |
| 213 | 213 | private function frequent(array $samples): array |
| 214 | 214 | { |
| 215 | - return array_values(array_filter($samples, function ($entry) { |
|
| 215 | + return array_values(array_filter($samples, function($entry) { |
|
| 216 | 216 | return $this->support($entry) >= $this->support; |
| 217 | 217 | })); |
| 218 | 218 | } |
@@ -287,7 +287,7 @@ discard block |
||
| 287 | 287 | */ |
| 288 | 288 | private function frequency(array $sample): int |
| 289 | 289 | { |
| 290 | - return count(array_filter($this->samples, function ($entry) use ($sample) { |
|
| 290 | + return count(array_filter($this->samples, function($entry) use ($sample) { |
|
| 291 | 291 | return $this->subset($entry, $sample); |
| 292 | 292 | })); |
| 293 | 293 | } |
@@ -302,7 +302,7 @@ discard block |
||
| 302 | 302 | */ |
| 303 | 303 | private function contains(array $system, array $set): bool |
| 304 | 304 | { |
| 305 | - return (bool) array_filter($system, function ($entry) use ($set) { |
|
| 305 | + return (bool) array_filter($system, function($entry) use ($set) { |
|
| 306 | 306 | return $this->equals($entry, $set); |
| 307 | 307 | }); |
| 308 | 308 | } |
@@ -120,7 +120,7 @@ |
||
| 120 | 120 | $this->dataType[$label][$i] = self::NOMINAL; |
| 121 | 121 | $this->discreteProb[$label][$i] = array_count_values($values); |
| 122 | 122 | $db = &$this->discreteProb[$label][$i]; |
| 123 | - $db = array_map(function ($el) use ($numValues) { |
|
| 123 | + $db = array_map(function($el) use ($numValues) { |
|
| 124 | 124 | return $el / $numValues; |
| 125 | 125 | }, $db); |
| 126 | 126 | } else { |
@@ -157,7 +157,7 @@ |
||
| 157 | 157 | protected function runTraining(array $samples, array $targets) |
| 158 | 158 | { |
| 159 | 159 | // The cost function is the sum of squares |
| 160 | - $callback = function ($weights, $sample, $target) { |
|
| 160 | + $callback = function($weights, $sample, $target) { |
|
| 161 | 161 | $this->weights = $weights; |
| 162 | 162 | |
| 163 | 163 | $prediction = $this->outputClass($sample); |
@@ -58,7 +58,7 @@ |
||
| 58 | 58 | protected function runTraining(array $samples, array $targets) |
| 59 | 59 | { |
| 60 | 60 | // The cost function is the sum of squares |
| 61 | - $callback = function ($weights, $sample, $target) { |
|
| 61 | + $callback = function($weights, $sample, $target) { |
|
| 62 | 62 | $this->weights = $weights; |
| 63 | 63 | |
| 64 | 64 | $output = $this->output($sample); |
@@ -190,7 +190,7 @@ discard block |
||
| 190 | 190 | * The gradient of the cost function to be used with gradient descent: |
| 191 | 191 | * ∇J(x) = -(y - h(x)) = (h(x) - y) |
| 192 | 192 | */ |
| 193 | - $callback = function ($weights, $sample, $y) use ($penalty) { |
|
| 193 | + $callback = function($weights, $sample, $y) use ($penalty) { |
|
| 194 | 194 | $this->weights = $weights; |
| 195 | 195 | $hX = $this->output($sample); |
| 196 | 196 | |
@@ -225,7 +225,7 @@ discard block |
||
| 225 | 225 | * The gradient of the cost function: |
| 226 | 226 | * ∇J(x) = -(h(x) - y) . h(x) . (1 - h(x)) |
| 227 | 227 | */ |
| 228 | - $callback = function ($weights, $sample, $y) use ($penalty) { |
|
| 228 | + $callback = function($weights, $sample, $y) use ($penalty) { |
|
| 229 | 229 | $this->weights = $weights; |
| 230 | 230 | $hX = $this->output($sample); |
| 231 | 231 | |