In this paper, we propose a new pruning method which is a combination of pre-pruning and
post-pruning, aiming on both classification accuracy and tree size. Based upon this method …

Classification is an important data mining task that discovers hidden knowledge from the
labeled datasets. Most approaches to pruning assume that all dataset are equally uniform …

In this paper, we introduce algorithms to voxelize polygonal meshes in common sampling
lattices. In the case of Cartesian lattices, we complete the separability and minimality proof …

C4. 5 algorithm is the most widely used algorithm in the decision trees so far and obviously
the most popular heuristic function is gain ratio. This heuristic function has a serious …

The development of computer technology has enhanced the people's ability to produce and
collect data. Data mining techniques can be effectively utilized for analyzing the data to …

With the development of computer technology and computer network technology, the degree
of information is getting higher and higher, people's ability of using information technology to …

Data mining is a process of extracting unknown or hidden knowledge from the existing data.
This is mainly used for predicting the future based on the past data. Classification in data …

Data Mining is a process of mining and extracting new information from a huge set of raw
data. Classification is a data mining technique that is used to classify each item in a data set …

The ever growing presence of data led to a large number of proposed algorithms for
classification and especially decision trees over the last years. Recently, it has been shown …

In this paper, we present a practical algorithm to deal with the data specific classification
problem when there are datasets with different properties. We proposed to integrate error …