[pre-commit.ci] pre-commit autoupdate (TheAlgorithms#8037)

* [pre-commit.ci] pre-commit autoupdate

updates:
- [github.com/MarcoGorelli/auto-walrus: v0.2.1 → v0.2.2](MarcoGorelli/auto-walrus@v0.2.1...v0.2.2)
- [github.com/PyCQA/isort: 5.10.1 → v5.11.3](PyCQA/isort@5.10.1...v5.11.3)

* updating DIRECTORY.md

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>

Author: 2 people

.pre-commit-config.yaml

@@ -10,7 +10,7 @@ repos:
       - id: requirements-txt-fixer
 
   - repo: https://github.com/MarcoGorelli/auto-walrus
-    rev: v0.2.1
+    rev: v0.2.2
     hooks:
     -   id: auto-walrus
 
@@ -20,7 +20,7 @@ repos:
       - id: black
 
   - repo: https://github.com/PyCQA/isort
-    rev: 5.10.1
+    rev: v5.11.3
     hooks:
       - id: isort
         args:

DIRECTORY.md

@@ -14,7 +14,6 @@
 
 ## Audio Filters
   * [Butterworth Filter](audio_filters/butterworth_filter.py)
-  * [Equal Loudness Filter](audio_filters/equal_loudness_filter.py)
   * [Iir Filter](audio_filters/iir_filter.py)
   * [Show Response](audio_filters/show_response.py)
 
@@ -79,6 +78,7 @@
   * [A1Z26](ciphers/a1z26.py)
   * [Affine Cipher](ciphers/affine_cipher.py)
   * [Atbash](ciphers/atbash.py)
+  * [Autokey](ciphers/autokey.py)
   * [Baconian Cipher](ciphers/baconian_cipher.py)
   * [Base16](ciphers/base16.py)
   * [Base32](ciphers/base32.py)
@@ -477,8 +477,6 @@
   * [Decision Tree](machine_learning/decision_tree.py)
   * Forecasting
     * [Run](machine_learning/forecasting/run.py)
-  * [Gaussian Naive Bayes](machine_learning/gaussian_naive_bayes.py)
-  * [Gradient Boosting Regressor](machine_learning/gradient_boosting_regressor.py)
   * [Gradient Descent](machine_learning/gradient_descent.py)
   * [K Means Clust](machine_learning/k_means_clust.py)
   * [K Nearest Neighbours](machine_learning/k_nearest_neighbours.py)
@@ -492,8 +490,6 @@
     * [Lstm Prediction](machine_learning/lstm/lstm_prediction.py)
   * [Multilayer Perceptron Classifier](machine_learning/multilayer_perceptron_classifier.py)
   * [Polymonial Regression](machine_learning/polymonial_regression.py)
-  * [Random Forest Classifier](machine_learning/random_forest_classifier.py)
-  * [Random Forest Regressor](machine_learning/random_forest_regressor.py)
   * [Scoring Functions](machine_learning/scoring_functions.py)
   * [Self Organizing Map](machine_learning/self_organizing_map.py)
   * [Sequential Minimum Optimization](machine_learning/sequential_minimum_optimization.py)