Analysis, Theory and Design of Logistic Regression Classifiers Used for Very Large Scale Data Mining By
نویسندگان
چکیده
This thesis is dedicated to my mother, who taught me that success is not the key to happiness. Happiness is the key to success. If we love what we are doing, we will be successful. This thesis is dedicated to my father, who taught me that luck is not something that is given to us at random and should be waited for. Luck is the sense to recognize an opportunity and the ability to take advantage of it. iii ACKNOWLEDGEMENTS I would like to thank my thesis committee –
منابع مشابه
Hybrid Method of Logistic Regression and Data Envelopment Analysis for Event Prediction: A Case Study (Stroke Disease)
Abstract Predictive analytics is an area of statistics that deals with extracting information from data and using it to predict trends and behavior patterns. Many mathematical modeling has been developed and used for prediction, and in some cases, they have been found to be very strong and reliable. This paper studies different mathematical and statistical approaches for events prediction. The ...
متن کاملClassification and Comparative Study of Data Mining Classifiers with Feature Selection on Binomial Data Set
This paper describes about the performance analysis of different data mining classifiers before and after feature selection on binomial data set. Three data mining classifiers Logistic Regression, SVM and Neural Network classifiers are considered in this paper for classification. The Congressional Voting Records data set is a binomial data set investigated in this study is taken from UCI machin...
متن کاملMaking Logistic Regression A Core Data Mining Tool
Binary classification is a core data mining task. For large datasets or real-time applications, desirable classifiers are accurate, fast, and automatic (i.e. no parameter tuning). Naive Bayes and decision trees are fast and parameter-free, but their accuracy is often below state-of-the-art. Linear support vector machines (SVM) are fast and have good accuracy, but current implementations are sen...
متن کاملSample size determination for logistic regression
The problem of sample size estimation is important in medical applications, especially in cases of expensive measurements of immune biomarkers. This paper describes the problem of logistic regression analysis with the sample size determination algorithms, namely the methods of univariate statistics, logistics regression, cross-validation and Bayesian inference. The authors, treating the regr...
متن کاملFinancial Reporting Fraud Detection: An Analysis of Data Mining Algorithms
In the last decade, high profile financial frauds committed by large companies in both developed and developing countries were discovered and reported. This study compares the performance of five popular statistical and machine learning models in detecting financial statement fraud. The research objects are companies which experienced both fraudulent and non-fraudulent financial statements betw...
متن کامل