In this project we are using weka tool for analyzing the efficiency of different algorithm.Weka tool can be useful for calculating the efficiency of the data set and obtaining better results.The ...

Implement a desktop application by using WEKA library (C# application for WEKA.dll or Java for WEKA.jar) to obtain the suitable dataset content for each classification algorithm. For example; • For ...

The implementation of AdaBoostM1 in Weka is a bit confusing because it does not directly follow the authors' original pseudocode as presented in class. The resulting Weka algorithm is mathematically ...

Achieving enlightenment through the process of learning highly frolics between what it is to remember and to forget. Without memories, we would have no evidence of what we knew, know, or what we might ...

Abstract: This decision tree is normally applicable in data mining in order to produce a framework that predicts the value of object or its dependent variable, established on the various input or ...

The amount of data in the world and in the people lives seems ever-increasing and there’s no end to it. The authors are overwhelmed with data. The WWW overwhelms the user with information. The Weka ...

ABSTRACT: Over the years, the amount of information about patients and medical information has grown substantially. Moreover, due to an increase of blood diseases patients, conventional diagnostic ...

Abstract: K-Nearest-Neighbor (KNN) as an important classification method based on closest training examples has been widely used in data mining due to its simplicity, effectiveness, and robustness.

Consumption of the electric power highly depends on the Season under consideration. The various means of power generation methods using renewable resources such as sunlight, wind, rain, tides, and ...