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Implement machine learning algorithms with python without sklearn.

Project description

Introduction

Implement machine learning algorithms with python without sklearn. Some classes are design especially for CQU-ML course by Professor.He

Install

  • With pip : pip3 install cquai-ml
  • With src : Clone or fork this project, then build it with python3 setup.py install

Usage

In most cases, API in this project is similar to scikit-learn project.

For example, if you want to run a decision tree classifier based on C4.5 (While scikit-learn use opt-CART instead of C4.5)

from cquai_ml import DecisionTreeClassifier
from sklearn.datasets import load_breast_cancer # get a dataset

X, y = load_breast_cancer(return_X_y=True)

clf1 = DecisionTreeClassifier(max_depth=1).fit(X, y)
pred1 = clf1.predict(X)

Contributing

Everyone is welcomed to contribute!

We currently provides:
  • DatasetSpace
  • UnionHypothesisSpace
  • LinearRegression
  • LogisticRegression
  • LinearDiscriminantAnalysis
  • KNeighborsClassifier
  • DecisionTreeRegressor
  • DecisionTreeClassifier

Project details


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Files for cquai-ml, version 1.0.7
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