A simple package to perform classification on a given dataset in csv or excel format
Project description
Machine Learning Classification Python Package
Functionality of the Package
-
Performs Classification using the following algorithms with the default parameters:
- LogisticRegression
- KNeighborsClassifier
- DecisionTreeClassifier
- RandomForestClassifier
- GradientBoostingClassifier
- SVC
- GaussianNB
- BernoulliNB
- MultinomialNB
-
Returns a results dataframe that has information of the model name, accuracy and F1-score on the test data.
-
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 versionpip 19.2.3
. - In case of error, feel free to contact me over Linkedin at Adnan.
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