Mathematics and Computer Science, Volume 1

20Predictive Analysis of Stock Prices Through Scikit-Learn: Machine Learning in Python

Vikash Kumar Mishra¹*, Richa Binyala², Pratibha Sharma² and Simran Singh²

¹SCSE, Galgotias University, Uttar Pradesh, India

²School of Business and Management, Christ (Deemed to be University), Delhi NCR, India

Abstract

Scikit-learn, a tool for developing machine learning algorithms, is a standard library of python. Through Scikit-learn, a trained model for predictive analysis can be developed. Such models aim to provide accurate predictions. Stock predictions are based on changes and patterns identified in the historical dataset. Following the trends and patterns of the historical changes of stocks, machine learning algorithms can be developed for achieving accurate outcomes. An effective model is developed, which enhance the working pattern or performance of the machine that further helps to draw a precise analysis of stocks.

Keywords: Predictive analysis, Scikit-learn, machine learning, stock market

20.1 Introduction

Scikit-learn is one of the libraries in python that serves as a robust tool for the branch of artificial intelligence and machine learning. Machine learning focuses on the use of data and algorithms to imitate the way humans learn, which gradually improves its accuracy. One of the major functions of machine learning is predictive analysis, meaning the system uses the data to predict what will happen in the future [1]. Accurate predictions can be achieved through machine learning ...