• Corpus ID: 40409471

An Exploration of Classification prediction techniques in data mining: the insurance domain

  title={An Exploration of Classification prediction techniques in data mining: the insurance domain},
  author={Samuel O. Danso},

Predicting Maternal Mortality Rate Using Data Mining Techniques: The Case of Jimma University Specialized Hospital Maternity Wards

This study is proved that the prediction of maternal mortality rate can be applicable with the help of da ta mining application in the maternity ward and predicting model for the life status of mothers after delivery has been already identified.

Towards Prediction of Students’ Academic Performance in Secondary School Using Decision Trees

The study found out that J48 Decision Tree classifier predicted students’ academic performance with higher accuracy than Naïve Bayes and Neural Networks classifiers.

Financial Trends prediction using the Back Propagation Neural Network and YQL

A back propagation neural network based system is used to estimate the stock value and the implemented classifier is used for forecasting the upcoming stock market values.

Classifying sentiments of twitter data using Bay’s neural network

A supervised hybrid classification technique is developed using the Bay’s classifier and the Back propagation neural network to find the emotional components of the micro-blog text according to the text sentiments and emotional features.

A Comparative Study in Data Mining: Clustering and Classification Capabilities

A detailed study on the data mining field takes place, followed by a comparative study between clustering and classification techniques, resulting that the integration of clusteringand classification techniques can provide more accurate results than a simple classification technique that classifies datasets with priorly known attributes and classes.

A Hybrid Data Model for Prediction of Disaster using Data Mining Approaches

A new data model is proposed which collect the real world knowledge from the web data sources and use with the data mining algorithms for predicting the unpredictable natural disasters and the results show the presentation of the futuremethod is accurate and efficient for prediction with any kind of other data also.

Financial Trends prediction using the Back Propagation Neural Network and YQL

The proposed system is an enhanced version of the traditionally available back propagation neural network which is compared with the traditional BPN model and the performance is found improved and adoptable.

A graph theoretic approach to control the traffic congestion on road network

A graph theoretic approach to control the traffic congestion on road network and a conceptual technique to facilitate the AJAX-based rich Internet application development are presented.

Final Grade Prediction of Secondary School Student using Decision Tree

J48 decision tree algorithm is applied on student previous result data to build a model in the form of decision tree which can predict the student final grade and will enable them to take preventive measure.

Suggested Marketing Strategy Using Apriori and FP-Growth Algorithms in retail sales in Egypt

Due to the increase of retail sales in Egypt and all over the world, came the importance for the managers of supermarkets to develop marketing strategy to maximize their profits, by getting rid of




The goal of this tutorial is to provide an introduction to data mining techniques appropriate for mining massive datasets using techniques from scalable and high performance computing.

Pattern Classification

Classification • Supervised – parallelpiped – minimum distance – maximum likelihood (Bayes Rule) > non-parametric > parametric – support vector machines – neural networks – context classification •

An Introduction to Variable and Feature Selection

The contributions of this special issue cover a wide range of aspects of variable selection: providing a better definition of the objective function, feature construction, feature ranking, multivariate feature selection, efficient search methods, and feature validity assessment methods.

Ensemble Methods in Machine Learning

Some previous studies comparing ensemble methods are reviewed, and some new experiments are presented to uncover the reasons that Adaboost does not overfit rapidly.

A Comparative Study on Feature Selection

  • 2002

Task and Results: Predicting and Explaining Caravan Policy Ownership

  • CoIL Challenge
  • 2000

Applied Logistic Regression

Applied Logistic Regression, Third Edition provides an easily accessible introduction to the logistic regression model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables.

Nonlinear estimation and classification

Nonlinear Classification * Approximation Theory and Signal Processing * Modeling of Complex Objects * Splines Gaussian Processes and Support Vector Machines * Case Studies * Theory * Machine Learning

Toward Optimal Feature Selection for Word Sense Disambiguation

A method for feature selection which is used for disambiguating word senses by applying a machine learning technique, which shows that the performance of the method is comparable to the existing sense disambIGuation techniques.

Neural networks in business: a survey of applications (1992–1998)