Identify drift in data set relating to ML
Budget: £10 – £20 GBP
I'm trying to do some work relating to explainable AI through data management. So I have this dataset:
https://archive.ics.uci.edu/ml/datasets/gas+sensor+array+drift+dataset
I am trying to write some code which will identify drift within the data set (potentially using the Kolmogorov-Smirnov (KS) or by plotting over time and see drift). I have written some preprocessing code for the data set also developed an SVM model which then tests for accuracy.
The idea I have is that my removing the drift in the data the accuracy of the model will increase. So I need help writing some code to show the drift in the data set and create some sort of visualisation that will show the drift.
Coding language is python.
Please see attached files for the code I have already done.
https://archive.ics.uci.edu/ml/datasets/gas+sensor+array+drift+dataset
I am trying to write some code which will identify drift within the data set (potentially using the Kolmogorov-Smirnov (KS) or by plotting over time and see drift). I have written some preprocessing code for the data set also developed an SVM model which then tests for accuracy.
The idea I have is that my removing the drift in the data the accuracy of the model will increase. So I need help writing some code to show the drift in the data set and create some sort of visualisation that will show the drift.
Coding language is python.
Please see attached files for the code I have already done.
Related categories:
Python
Data Processing
Software Architecture
Machine Learning (ML)
Big Data Sales