Scientific Journals Influence Scores Prediction

At-a-Glance 👀

Data Preparation for Machine Learning: Scientific Journals Influence Scores Prediction

Purpose

This project focuses on the initial stage of preparing a dataset for a machine learning model aimed at predicting the influence scores of scientific journals

Background

This is a regression problem where the outcome variable is the projected article influence score. The dataset involves information from various sources, including researchers, web scraping, and publishers, featuring details such as journal ISSN, title, publisher, subscription price, and article influence scores.

Objectives

Within this project, I would like to explore the following:

Data Cleaning:Identify and correct issues in the dataset to prepare it for machine learning analysis. This includes handling missing values, identifying and fixing data inconsistencies, and ensuring data quality.

Data Integration: Combine information from three separate files into a single dataset, ready for analysis.

Exploratory Data Analysis (EDA):Perform a preliminary analysis to understand the dataset's structure, variables, and potential issues.

Data-Preparation-for-Machine-Learning

Fideladdi • Updated Sep 6, 2024