This is a python module which is made for learning purpose.
Project description
PyStatsLearn
This is a python module which is made for education purpose. The aim is to implement machine learning algorithms and publish it. Currenlty this package has 2 functionalities
- Calculating mean by taking a dataframe as an input. (Mean Calculates is not done by using any library. The code is developed from scratch)
- Implemeted Gaussian Naive Bayes Classifier which is build upon numpy
Installation
pip install PyStatsLearn
Usage
import pandas as pd
from PyStatsLearn import Measure, GaussianNaiveBayesClassifier
from sklearn.model_selection import train_test_split
df = pd.read_excel('data.xlsx')
a = Measure(df)
print(a.mean('Insulin'))
b = GaussianNaiveBayesClassifier()
X = df.iloc[:, :-1]
y = df.iloc[:, -1]
X = X.to_numpy()
y = y.to_numpy()
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=.25)
nb_classifier = GaussianNaiveBayesClassifier()
nb_classifier.train(X_train, y_train)
predictions = nb_classifier.predict(X_test)
print(predictions)
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