To Improve the Accuracy in Identifying Breast Cancer Using Various Techniques of Big Data Analysis.

Abstract

In present, breast cancer in women is most is the prominently discovered life-threatening cancer in women and took over too many life's of women all around the world. This project deals with the Breast Cancer Wisconsin dataset to compare the accuracy of various machine learning algorithm in predicting the breast cancer in women. The various classification model are built and trained with the Wisconsin dataset. The different classifiers that are used to construct the model are Naive Bayes, Support Vector Machine, Regression Tree, Random Forest and K-Nearest Neighbor. The efficient working of these model are assessed by estimating the accuracy score of each model with the usage of unstandardized and standardized dataset. Once the performance of the model are evaluated, the optimal working algorithm are used to identify the type of breast cancer in the patient entry.

Sports Big Data Analysis Based on Cloud Platform and Its Impact on Sports Economy

“…If you want to make the points in the training set as far as possible from the classifier, find an optimal classifier to maximize the blank area on both sides of it [16]. en, the optimal classifier should satisfy the following formula:…”

Prevention and Resolution of Hidden Market Behaviors in Sports Events

“…Its economic value can be divided into: the value of sports events itself, the value of sports events driving or promoting, and the social evaluation value of sports events. The value of sports events itself comes from the elements of the events, which is the most easy factor to -16-promote consumers to generate related consumption, and also the core part of the marketing activities related to the events carried out by major sponsors and hidden marketers, such as souvenirs of the events and consumer goods with elements of the events [4]. The core of the promotion value of sports events is the media attention rate, that is, to improve their own market awareness and brand value through media publicity.…”