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Created over 5 years ago
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rahulmadanraju

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The following gives information regarding the Particle Swarm Optimizer for feature selection process using various machine learning classifiers within the classification function

Metaheuristic-Binary-Optimizer-for-Feature-Selection---BPSO

The binary version of this meta-heuristic optimizer is used for feature selection process through a wrapper based method. The Optimizer is set with a threshold value, provided they consider the random subset of data over each iteration and train the system and finally land up with minimum feature subset with best classification accuracy

MATLAB

Semantic-Search-Engine

Jupyter Notebook

Implementation-and-Optimizations-using-KNN-Machine-Learning-Algorithms

Implementation of machine learning algorithms for the evaluation of data from the wearable sensors such as FSR, EMG and Strain Gauge which are used for the classification purpose of various sign recognitions

MATLAB

Projects

The folder contains the list of projects worked on Machine Learning, Deep Learning, Natural Language Processing, Computer Vision and other Libraries like scikit learn, tensorflow, keras, numpy, pandas, matplotlib, pillow, openCV, etc.

Jupyter Notebook

Signal-Conditioning-Arduino

Master Control Circuit

C++

Machine-Learning-Engineer-Udacity

Jupyter Notebook

MERIDA

Jupyter Notebook

Metaheuristic-Optimizer-for-Feature-Selection

MATLAB

LeetCode

Python

Summarizers

#summariation #abstractivesummarization #extractivesummarization #nlp #machinelearning

Python

rahulmadanraju/Metaheuristic-Optimizer-for-Feature-Selection---PSO

rahulmadanraju

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