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Machine Learning Classification Python Package

Functionality of the Package

  1. Performs Classification using the following algorithms with the default parameters:

    • LogisticRegression
    • KNeighborsClassifier
    • DecisionTreeClassifier
    • RandomForestClassifier
    • GradientBoostingClassifier
    • SVC
    • GaussianNB
    • BernoulliNB
    • MultinomialNB

  2. Returns a results dataframe that has information of the model name, accuracy and F1-score on the test data.

  3. The package takes the following parameters as input:

    • dataset_path: Path to the csv or excel dataset.
    • output_column: Name of the output column which contains the target variable.
    • train_test_ratio: Ratio in which the dataset is to be divided in train and test splits.

Usage

  • Make sure you have Python installed in your system.
  • Run Following command in the CMD. 
    pip install classifier_agent

Example

from classifier_agent import classifier_agent

dataset_path = "diabetes.csv"
output_column = "Outcome"
train_test_ratio = 0.25

results = classifier_agent(dataset_path, output_column, train_test_ratio)
print(results)

Note

  • The package is currently in a very elementary stage and work is in progress.
  • The whole project is developed with python version Python 3.7.7 and pip version pip 19.2.3.
  • In case of error, feel free to contact me over Linkedin at Adnan.