Implementation of Logistic Regression and SVM for Titanic Survival Prediction using Python |
Author(s): |
| Swayanshu Shanti Pragnya , Centurion University |
Keywords: |
| Data Analysis, Machine Learning, Data Munging, Logistic Regression, SVM, Prediction, Confusion Matrix |
Abstract |
|
Predictive analysis is the new era of statistics but still requires human interface for facing more critical problems like every human does in their day to day life. The enhancement in problem solving capability leads to come up with new technique in terms of machine learning algorithms. Evaluation as well as accuracy is primarily concerned with data analysis and prediction of data. But before prediction collection, identification, segregation and pattern identification is important for data analysis. So for that, machine learning algorithms are designed to solve such problems. This paper is primarily concerned for knowing the basic about these algorithms and executing the accuracy of data prediction in Logistic regression and Support vector machine (SVM) algorithm with full code using python. Here we will also introduce confusion matrix for result analysis. |
Other Details |
|
Paper ID: IJSRDV6I21169 Published in: Volume : 6, Issue : 2 Publication Date: 01/05/2018 Page(s): 2172-2175 |
Article Preview |
|
|
|
|
