Go metrics for calculating string similarity and other string utility functions

TreeMinHash: Fast Sketching for Weighted Jaccard Similarity Estimation

This project aims to predict liver disease in Indian patients

Kotlin multiplatform library offering various algorithms to measure string similarity and distance

Breast ultrasound (BUS) image segmentation using region-growing algorithm

Fast Jaccard similarity search for abstract sets (documents, products, users, etc.) using MinHashing and Locality Sensitve Hashing

Different clustering and clustering metrics are implemented in this repository

Built a classifier to predict whether a loan case will be paid off or not. Used classification algorithms (k-Nearest Neighbour, Decision Tree, Support Vector Machine, Logistic Regression). Each result is reported with the accuracy of each classifier (Jaccard index, F1-score, LogLoass)

HyperLogLog en C++ y OpenMP para cálculo de similitud de genomas mediante índice de Jaccard

load a dataset using Pandas and apply the following classification methods (KNN, Decision Tree, SVM, and Logistic Regression) to find the best one by accuracy evaluation methods (Jaccard, F1-score, LogLoss) for this specific dataset.

Classifying images into discrete categories based on keywords generated from the Google Cloud Vision API

The Dice Coefficient Is Scale Sensitive, Mathematical Proof.

We load a historical dataset from previous loan applications, clean the data, and apply different classification algorithms on the data.

Testing Jaccard similarity and Cosine similarity techniques to calculate the similarity between two questions.

An R script that uses MACCS166 chemical fingerprint and calculates Jaccard Index/Tanimoto Coefficient for a list of Aspartate Racemase Ligands

Document Comparison web application based on Jaccard Similarity Index. The uploaded file is compared to all previously uploaded ones. Built with Java/JSP

This project contains the KNN, SVM, Logistic Regression and Decision Tree algorithms applied to a loan data set. Model Evaluation is also presented at the end of this model.

This code generate partitions for a multilabel dataset using the Jaccard Index similarity measure. We use HCLUST with 6 linkage metrics to generate several partitions. You may build the partition with the highest coefficient. This code also provide an analysis about the partitioning.

Implementation of various machine learning techniques to detect credit card frauds based on a given dataset. This repo will guide you through the data analysis, viz and building predictive models

Using Spark In Python For Movie Similarities With Jaccard Index