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.