Logistic regression methods for classification of imbalanced data sets

Logistic regression methods for classification of imbalanced data sets

Classification of imbalanced data sets is one of the important researches in Data Mining community, since the data sets in many real-world problems mostly are imbalanced class distribution. This thesis aims to develop the simple and effective imbalanced classification algorithms by previously improv...

Saved in:

书目详细资料
主要作者:	Santi Puteri Rahayu, -
格式:	Thesis
语言:	English
出版:	2012
主题:	QA Mathematics
在线阅读:	http://umpir.ump.edu.my/id/eprint/3649/1/Logistic%20regression%20methods%20for%20classification%20of%20imbalanced%20data%20sets.pdf
标签:	添加标签没有标签, 成为第一个标记此记录!

相似书籍

Classification for large number of variables with two imbalanced groups
由: Ahmad Hakiim, Jamaluddin
出版: (2020)

An enhanced resampling technique for imbalanced data sets
由: Maisarah, Zorkeflee
出版: (2015)

Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
由: Saeed, Sana
出版: (2019)

Embedded feature selection methods with high dimensionality for elastic net and logistic regression models
由: Alharthi, Aiedh Mrisi
出版: (2022)

Mathematics graduates perceptions on suitability of employment using logistic regression
由: Jamri, Heirnizah Melati
出版: (2014)

Using rough set through for classification of image segmentation data
由: Diallo Abdoulaye, Kindy
出版: (2014)

New Test Statistics To Assess The Goodness-Of-Fit Of Logistic Regression Models
由: Hussain, Jassim Nassir
出版: (2013)

An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis
由: Ong, Phaik Ling
出版: (2016)

Classification and regression tree in classifying and predicting students' academic performance
由: Ho, Su Juih
出版: (2013)

Binary logistic regression modelling with appropriate sample size in determining graduate employability factors for public universities in Malaysia
由: Tengku Mohamed, Tengku Salbiah
出版: (2020)

Customer churn classification in telecommunication company using rough set theory
由: Nur Syafiqah, Mohd Nafis
出版: (2016)

Linear regression for data having multicollinearity, heteroscedasticity and outliers
由: Rasheed, Bello AbdulKadiri
出版: (2017)

Robust PRIDIT scoring method for classification fraud cases in financial data
由: Tukiman, Norbaiti
出版: (2022)

Count data analysis using poisson regression and handling of overdispersion
由: Zainordin, Raihana
出版: (2009)

Mining Students' Data with Holland Model Using Neural Network and Logistic Regression
由: Noorlin, Mohd. Ali
出版: (2005)

Statistical inference in logistic regression models /
由: Wu, Swee Leng
出版: (2011)

Prediction Of Musculoskeletal Disorders Cases Associated With Work-Relatedness Of Semiconductor Workers Using Logistic Regression Model
由: Chai, Fong Ling
出版: (2020)

Multinomial logistic regression probability ratio-based feature vectors for Malay vowel recognition
由: Atanda, Abdulwahab Funsho
出版: (2021)

AK-means geometric smote with data complexity analysis for imbalanced dataset
由: Nur Athirah, Azhar
出版: (2023)

Mammogram images classification based on fuzzy soft set
由: Anwar Lashari, Saima
出版: (2016)

Generative Adversarial Network and Fuzzy ARTMAP for imbalanced data classification in condition monitoring
由: Chang, Timothy Zhi Wei
出版: (2023)

Classification of imbalanced datasets using naive bayes
由: Mohd. Sobran, Nur Maisarah
出版: (2011)

Rough set approach for categorical data clustering
由: Herawan, Tutut
出版: (2010)

Bootstrap confidence intervals for the mode of log-logistic hazard function
由: Hasan, Siti Normah
出版: (2009)

Two-dimensional Stefan problem using level set method
由: Noor Azhuan, Nur Azura
出版: (2017)

An enhanced robust association rules method for missing values imputation in Arabic language data set
由: Salem, Awsan Thabet
出版: (2023)

Modification Of Regression Models To Solve Heterogeneity Problem Using Seaweed Drying Data
由: Joshua, Ibidoja Olayemi
出版: (2023)

Modified logistic model for mortality rates in Malaysia
由: Ah Khaliludin, Nur Idayu
出版: (2021)

An efficient implementation of Runge-Kutta Gauss methods using variable stepsize setting
由: Sara Syahrunnisaa Mustapha
出版: (2021)

A study of an improved two-step learning artificial neurel network for imbalanced data set problem
由: Che Shamsudin, Hasrul
出版: (2011)

Robust diagnostic and estimation for binary logistic regression model in the presence of multicollinearity and high leverage points
由: Ariffin @ Mat Zin, Syaiba Balqish
出版: (2018)

Feature selection for traditional Malay musical instrument sound classification using rough set
由: Senan, Norhalina
出版: (2013)

Enhancing Model Selection Based On Penalized Regression Methods And Empirical Mode Decomposition
由: Al Jawarneh, Abdullah Suleiman Saleh
出版: (2021)

Duplicates detection approach within incomplete data sets using dynamic sorting key and hot deck compensation method
由: Abdulrahim, Abdulrazzak Ali Mohamed
出版: (2022)

Modified method for removing multicollinearity problem in multiple regression model
由: Yap, Sue Jinq
出版: (2014)

Data sampling methods on imbalanced datasets for pneumonia detection in covid-19 patients
由: Dzulkefli, Syasya Farina
出版: (2022)

Hybrid Model In Machine Learning With Robust Regression For Handling Multicollinearity Outlier In Big Data And Its Application To Agriculture
由: ., Mukhtar
出版: (2023)

Statistical downscaling using regression-based technique in Peninsular Malaysia
由: Kho, Pui Kim
出版: (2020)

Multiple linear regression and neural network for electric load forecasting
由: Kamisan, Nur Arina Bazilah
出版: (2017)

Central double cross-validation for estimating parameters in regression models
由: Chye, Rou Shi
出版: (2016)

Services hosted by the Perpustakaan Sultan Abdul Samad, Universiti Putra Malaysia with Cooperation MySyL Group