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Гералд Бирген gbrigens

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gbrigens / Survey.md
Last active March 20, 2024 17:42
A Survey of Machine Learning’s Integration into Traditional Software Risk Management

Cleaning Data

Appendix: Data Cleaning

To remove duplicates and clean titles to make the data suitable for further analysis. Data cleaning is a fundamental aspect of data analysis and is particularly important when working with real-world datasets, which often contain missing, duplicate, or inconsistent records. We provide detailed steps and rationale behind the steps.

The data-cleaning process is broken down into two major steps:

  1. Duplicate Removal: Removing duplicate entries based on multiple criteria.
  2. Title Cleaning: Removing conference proceeding information from the titles.
@gbrigens
gbrigens / pointerlab.cpp
Last active January 26, 2022 22:35
Pointers in C++
#include <iostream>
#include <string>
using namespace std;
struct Student {
string name;
int id;
int marks[3];
};
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gbrigens / resultType.swift
Created January 5, 2020 22:25
Swift5 Result Type
struct HolidayResponse: Codable {
let response: Holidays
}
struct Holidays: Codable {
let holidays: [HolidayDetail]
}
struct HolidayDetail:Codable {
let name: String
let date: HolidayDate