The project conatins Gaussian Naïve Bayes and Logistic Regression to classify the Spambase data
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Updated
Jun 1, 2018 - Python
The project conatins Gaussian Naïve Bayes and Logistic Regression to classify the Spambase data
Predict the onset of diabetes based on diagnostic measures by Naive Bayes Classifier Algorithm
Predicts the iris-plant-type using Naive Bayes algorithm and iris plant dataset from https://archive.ics.uci.edu/ml/datasets/iris
Compound NLP GUI project, First used many ML algorithmes (SVM,Logistic Regression...etc) for nlp tasks like "News Classification",seconedly used specialized NLP tools for task like "Text Summerization",Thirdly used Deep Learning for NLP task like"Machine Translation",fourthly web scraping and pre-trained models for task"Code Generation"
Data is a Drag: Exploring Classical Machine Learning Algorithms on Small and Imbalanced Datasets
Predicting Loan Defaults using 15+ Features and over 250,000 records
A Sentiment Analysis Application Using Naive Bayes classifier
Implementation of Naive Bayes from scratch using Python
A program that classifies bank transactions into legitimate and fraudulent transactions.
Email-Spam-Classifier using Naive Bayes Algorithm
Naive Bayes classification model (study only)
Breast Cancer Data Analysis: Analyzes and classifies breast cancer data using a Naive Bayes classifier with preprocessing, label encoding, and k-fold cross-validation. Cars Dataset Analysis: Explores a cars dataset with data loading, statistics, and visualizations, including price distribution and correlation heatmap. Hayes-Roth Classification: C
Naive Bayes Example
Explore the vast field of Natural Language Processing (NLP) with our comprehensive toolkit. From text preprocessing to advanced sentiment analysis and language modeling, this repository provides a range of tools and algorithms to empower your NLP projects. Dive into state-of-the-art techniques and resources curated to enhance your understanding.
Prediction the hospital readmissions for diabetes patients
Email Spam Classifier will help people identify Spam E-Mails similar to the Spam encountered earlier, which are stored in a vast library of Spam E-Mails. This product will also help in identifying new Potential Spam E-Mails from known & unknown sources.
In this resource, I will guide you through various projects where I employ diverse Classification Algorithms in Machine Learning to tackle a range of business problems.
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