MLfromScratch

Library for machine learning where all algorithms are implemented from scratch. Used only numpy.

Here I tried to keep package modules in same structure as sklearn.

Package Description

  1. linear_model
    • LinearRegression
    • SGDRegressor
    • SGDClassifier
  2. tree
    • DecisionTreeClassifier
    • DecisionTreeRegressor
  3. neighbors
    • KNeighborsRegressor
    • KNeighborsClassifier
  4. naive_bayes
    • GaussianNB
    • MultinomialNB
  5. cluster
    • KMeans
    • AgglomerativeClustering
    • DBSCAN
    • MeanShift
  6. ensemble
    • RandomForestClassifier
    • RandomForestRegressor
    • GradientBoostingRegressor
    • GradientBoostingClassifier
    • VotingClassifier
  7. metrics
    • mean_squared_error
    • root_mean_squared_error
    • mean_absolute_error
    • r2_score
    • accuracy_score
    • confusion_matrix
    • roc_auc_score
    • roc_curve
    • precision_score
    • recall_score
    • sensitivity_score
    • specificity_score
    • f1_score
    • adjusted_rand_score
  8. model_selection
    • train_test_split
    • KFold
  9. preprocessing
    • StandardScaler
    • MinMaxScaler
    • RobustScaler
    • LabelEncoder
    • OneHotEncoder

Contributors

Mlfromscratch

Library for machine learning where all algorithms are implemented from scratch. Used only numpy.

Mlfromscratch Info

⭐ Stars 14
🔗 Source Code github.com
🕒 Last Update 6 months ago
🕒 Created 3 years ago
🐞 Open Issues 0
➗ Star-Issue Ratio Infinity
😎 Author adityajn105