ML-390 Typo fixes

Author: apphp

docs/neural-network/optimizers/cyclical.md

@@ -11,7 +11,7 @@ $$
 \text{cycle} &= \left\lfloor 1 + \frac{t}{2\,\text{steps}} \right\rfloor \\
 x &= \left| \frac{t}{\text{steps}} - 2\,\text{cycle} + 1 \right| \\
 \text{scale} &= \text{decay}^{\,t} \\
-\eta_t &= \text{lower} + (\text{upper} - \text{lower})\,\max\bigl(0\,1 - x\bigr)\,\text{scale} \\
+\eta_t &= \text{lower} + (\text{upper} - \text{lower})\,\max\bigl(0,1 - x\bigr)\,\text{scale} \\
 \Delta\theta_t &= \eta_t\,g_t
 \end{aligned}
 $$

docs/neural-network/optimizers/rms-prop.md

@@ -15,11 +15,11 @@ $$
 $$
 
 where:
-- $g_t$ - is the current gradient,
-- $v_t$ - is the running average of squared gradients,
-- $\rho$ - is the averaging coefficient ($1 − decay$),
-- $\eta$ - is the learning rate ($rate$),
-- $\varepsilon$ - is a small constant to avoid division by zero (implemented by clipping $\sqrt{v_t}$ to $[ε, +∞)$).
+- $g_t$ is the current gradient,
+- $v_t$ is the running average of squared gradients,
+- $\rho$ is the averaging coefficient ($1 − decay$),
+- $\eta$ is the learning rate ($rate$),
+- $\varepsilon$ is a small constant to avoid division by zero (implemented by clipping $\sqrt{v_t}$ to $[ε, +∞)$).
 
 ## Parameters
 | # | Name | Default | Type | Description |

src/NeuralNet/Optimizers/Cyclical.php

@@ -86,7 +86,7 @@ public function __construct(
 
         if ($lower > $upper) {
             throw new InvalidArgumentException('Lower bound cannot be'
-                . ' reater than the upper bound.');
+                . ' greater than the upper bound.');
         }
 
         if ($losses < 1) {

src/NeuralNet/Optimizers/Cyclical/Cyclical.php

@@ -90,7 +90,7 @@ public function __construct(
 
         if ($lower > $upper) {
             throw new InvalidArgumentException(
-                'Lower bound cannot be reater than the upper bound.'
+                'Lower bound cannot be greater than the upper bound.'
             );
         }
 

tests/NeuralNet/Optimizers/AdaGrad/AdaGradTest.php

@@ -1,6 +1,6 @@
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Rubix\ML\Tests\NeuralNet\Optimizers\AdaGrad;
 

tests/NeuralNet/Optimizers/Adam/AdamTest.php

@@ -1,6 +1,6 @@
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Rubix\ML\Tests\NeuralNet\Optimizers\Adam;
 

tests/NeuralNet/Optimizers/Momentum/MomentumTest.php

@@ -1,6 +1,6 @@
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Rubix\ML\Tests\NeuralNet\Optimizers\Momentum;