IJSRSET19651 | Received : 18 Nov 2019 | Accepted : 10 Dec 2019 | November-December-2019 [ 6 (6) : 113-118 ] © 2019 IJSRSET | Volume 6 | Issue 6 | Print ISSN: 2395-1990 | Online ISSN : 2394-4099 Themed Section : Engineering and Technology DOI : https://doi.org/10.32628/IJSRSET196634 113 A Novel Approach for improving Breast Cancer Prediction Using Wavelet based Feature extraction and SVM Madhuri Maru 1 , Prof. Saket Swarndeep 2 1 Information Technology Department, L.J. Institute of Engineering and Technology, Gujarat Technological University, Ahmedabad, Gujarat, India 2 Professor, L.J Institute of Engineering and Technology, Gujarat Technological University, Ahmedabad, Gujarat, India ABSTRACT Breast cancer represents one of the diseases that make a high number of deaths every year. It is the most common type of all cancers and the main cause of women’s deaths worldwide. Classification and data mining methods are an effective way to classify data. Especially in medical field, where those methods are widely used in diagnosis and analysis to make decisions. Here, a common misconception is that predictive analytics and machine learning are the same thing where in predictive analysis is a statistical learning and machine learning is pattern recognition and explores the notion that algorithms can learn from and make predictions on data. In this paper, we are addressing the problem of predictive analysis by adding machine learning techniques for better prediction of breast cancer. In this, a performance comparison between different machine learning algorithms: Support Vector Machine (SVM), Decision Tree (C4.5), Naive Bayes (NB) and k Nearest Neighbors (k-NN) on the Wisconsin Breast Cancer (original) datasets is conducted. The main objective is to assess the correctness in classifying data with respect to efficiency and effectiveness of hybrid algorithm in terms of accuracy, precision, sensitivity and specificity. Keywords : Breast Cancer, Machine learning Algorithms, Image processing, Convolution Neural Network (CNN) I. INTRODUCTION Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves. [17] Figure 1. Machine learning methods