[EXE] Intrusion detection system using machine learning

[Prasad-adhi]

Learning Goals

Binary classification with a class imbalance dataset

Exercise Statement

A 3D printer is assumed to be the device whose parameters are received from a server. The 3D printer is simulated to be a delicate machine that when few wrong parameters are loaded, the machine will fail. Thus, it is crucial for a system to detect whether the incoming data is valid or not. Since in the real world the probability of erroneous values is far lesser than the probability of valid data, the dataset is simulated to have only 8 - 10% of erroneous values. The goal is to have less number of false negatives while classification.

Prerequisites

Data preprocessing, Machine learning, Data visualization

Data source/summary:

Dataset_2000.csv
The dataset was simulated and created in python. I have the attached the simulated dataset in this issue

Solution

I have the solution for this and would be happy to create a pull request

[DhruvSanghvi2002]

Really interesting topic ,kindly assign me this issue @Prasad-adhi