Web Effort Estimation is a process of predicting the efforts and cost in terms of money, schedule and staff for any software project system. Many estimation models have been proposed over the last three decades and it is believed that it is a must for the purpose of: Budgeting, risk analysis, project planning and control, and project improvement investment analysis. In this paper, we investigat...

Classification is a data mining (DM) technique used to predict or forecast the unknown information using the historical data. There are many classification techniques. ID3 is a very popular tree based classification algorithm for a categorical data which does not support continuous data. Attribute selection process plays major role in building a classification tree model. Attribute Selection in...

This paper proposes a combinatorial method based on different clustering algorithms with ID3 decision tree classification for the classification of network anomaly detection. The idea is to detect the network anomalies by first applying any clustering algorithm to partition it into a number of clusters and then applying ID3 algorithm for the decision that whether an anomaly has been detected or...

OBJECTIVES This paper aims to predict childhood obesity after age two, using only data collected prior to the second birthday by a clinical decision support system called CHICA. METHODS Analyses of six different machine learning methods: RandomTree, RandomForest, J48, ID3, Naïve Bayes, and Bayes trained on CHICA data show that an accurate, sensitive model can be created. RESULTS Of the meth...

The establishment of distant metastases depends on the capacity of small numbers of cancer cells to regenerate a tumor after entering a target tissue. The mechanisms that confer this capacity remain to be defined. Here we identify a role for the transcriptional inhibitors of differentiation Id1 and Id3 as selective mediators of lung metastatic colonization in the triple negative [TN, i.e., lack...

Using an evolutionary approach for evolving classifiers can simplify the classification task. It requires no domain knowledge of the data to be classified nor the requirement to decide which attribute to select for partitioning. Our method, called the Genetic Evolved Classifier (GEC), uses a simple structured genetic algorithm to evolve classifiers. Besides being able to evolve rules to classif...

Gene knockout experiments in mice have suggested a hierarchical model of early B cell commitment wherein E2A proteins (E47 and E12) activate early B cell factor (Ebf1), which in turn activates expression of the B cell commitment factor, Pax5. In IL-7 receptor alpha (IL-7Ralpha) knockout mice, B cell development is blocked before B-lineage commitment at the prepro-B cell stage in adult animals. ...

We compare two types of knowledge representations for data mining: decision trees and knowledge rules, and three mining methods. We show that the decision tree representation and the knowledge rules representation are semantically equivalent. The ID3 algorithm by Quinlan has limited generalization power because it uses only a very simple generalization function of partial attribute removal type...