An android application that uses K Clustering, K means, KNN to automate career counseling 🎲 and provides up-to-date data about Pakistani universities. 📈
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Updated
Jan 19, 2022 - Java
An android application that uses K Clustering, K means, KNN to automate career counseling 🎲 and provides up-to-date data about Pakistani universities. 📈
Simple algorithm I used for clustering data in another project.
A Java console application that implemetns k-fold-cross-validation system to check the accuracy of predicted ratings compared to the actual ratings and RMSE to calculate the ideal k for our dataset.
A Java console application that implements the factionality of the knn algorithm to find the similarity between a new user's location preferences and the locations. The binary data (0,1) are the location characteristics.
Artificial Intelligence course at PJAIT
Classifying MIDI files using machine learning for Cornell CS 4780: Machine Learning. Collaboration with Chee Yong Lee.
Client Server Implementation of Distributed K-Nearest Neighbour Algorithm
A Java console application that implemetns k-fold-cross-validation system to check the accuracy of predicted ratings compared to the actual ratings.
this project provide the implementation of the knn (k-nearest neighbors) algorithm and a test on iris dataset
Form recognition
Simple kNN and NaiveBayes classifier implementation
In pattern recognition, the k-nearest neighbour's algorithm (k-NN) is a non-parametric method used for classification and regression.[1] In both cases, the input consists of the k closest training examples in the feature space. The output depends on whether k-NN is used for classification or regression: https://en.wikipedia.org/wiki/K-nearest_ne…
Project 1 (KNN-Algorithm)
Just a simple implementation of K-Nearest Neighbour algorithm.
K-Nearest Neighbor Text Categorization
Undergraduate Thesis Project with Kishore Rajendra under the guidance of Dr. Neminath Hubballi.
A Java console application that implements the factionality of the knn algorithm to find the similarity between a new user with only a few non zero ratings of some locations, find the k nearest neighbors through similarity score and then predict the ratings of the new user for the non rated locations.
Implementation of Machine Learning algorithms from scratch
The server for the "Framework for Indoor Positioning on Mobile Devices"
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