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Name: Abhra Gupta
Type: User
Company: DTU
Bio: Data Engineer
Location: New Delhi
Name: Abhra Gupta
Type: User
Company: DTU
Bio: Data Engineer
Location: New Delhi
The dataset used in the proposed work is obtained from the Department of Epileptology of the University of Bonn.The accuracy achieved in one of the Multi-class classification experiment in the proposed work is 98.45% which beats the state of the art accuracy in this three-class problem. Additionally, the proposed method has achieved highest accuracy of 100% in classifying normal EEG signals(eyes closed) and seizure EEG signal and an accuracy of 100% in classifying normal EEG signals(eyes open) and seizure EEG signal which is comparable with the existing state of the art EEG signal classification techniques. Six different classification techniques have been used in each of the five experiments conducted where every classification technique has been used with 8 different Daubechies wavelets db1 to db8. The results obtained from these experiments provide valuable insights establishing that SVM performs the best in most of the experiments with the db4 wavelet among the 8 wavelets achieving the highest accuracy
Perform operations on a dataset in Pyspark and export it to MySQL database
This repository contains Ipython notebooks of assignments and tutorials used in the course introduction to data science in python, part of Applied Data Science using Python Specialization from University of Michigan offered by Coursera
This project discusses concentrates on pattern classification system. In this report, two classifiers have been discussed namely Minimum Distance classifier and Mahalanobis Distance classifier. Four popular real- valued datasets which consist of data from two classes are used to evaluate the performance of both the Mahalanobis distance classifier and the Minimum distance Classifier. The two classifiers are evaluated on the basis of Accuracy, Precision, Recall and F-measure. It is seen that the Mahalanobis distance classifier outperforms the Minimum distance Classifier in these five datasets.
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