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Machine Learning based predictive analysis model for malaria infected cell detection

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Machine Learning Predictive Analysis MalariaDetection

Introduction

The data is image of healtly cells and cells infected with malaria. A healtly cell do not have any blob, whereas a infected cells image has few blog in it. We use opencv to process on the image data to convert to get the conture of these cells. And, then build a random forest classifier model for our predictive ananlysis.

How to setup

1. download and extract data set from https://drive.google.com/file/d/1azIYjzLFCY7qp7-NjgSBvakbGgPvQlRf/view.
2. Generate_DataSet.py file process the image files to generate a datafram in cvs file.
3. Run ML_PredictiveAnalysis_MalariaDetection.py to build and train the model.

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Machine Learning based predictive analysis model for malaria infected cell detection

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