Raihan's Journal

From Matthew North (Data Mining for the Masses) Chapter 10/Decision Tree, Page 157-174 Using Decision Tree model in order to find good early predictors of buying behavior, and there is a rich data set of information, including items they have just browsed for, and those have actually purchased. With following attributes : User_ID, Gender, Age, Marital_Status, Website_Activity, Browsed_Electronics_12Mo, Bought_Electronics_12Mo, Bought_Digital_Media_18Mo, Bought_Digital_Books, Payment_Method, eReader_Adoption. The Results the complete process before press "play" button decision tree graph result in apply model data description of decision tree result in apply model statistics

Classification Method Data Mining classification Classification techniques in data mining are capable of processing a large amount of data. It can be used to predict categorical class labels and classifies data based on training set and class labels and it can be used for  classifying newly available data.The term could cover any context in which some decision or forecast is made on the basis of presently available information. Classification procedurs recognized method for repeatedly making such decisions in new situations. Here if we assume that problem is a concern with the construction of a procedure that will be applied to a continuing sequence of cases in which each new case must be assigned to one of a set of pre defined classes on the basis of observed features of data.Creation of a classification procedure from a set of data for which the exact classes are known in advance is termed as pattern recognition or supervised learning. Contexts in which a classificatio...

Rapid Miner In this blog i will use rapid miner as my prediction by using data pemilu dataset. RapidMiner is a software platform developed by the company of the same name that provides an integrated environment for machine learning, data mining, text mining, predictive analytics and business analytics. I will use three main algorithms, which are; Decision Tree (C4.5), Naïve Bayes (NB) and K-Nearest Neighbor (K-NN). 1. Decision Tree  The Decision Tree the decision tree description the performance vector   So, Decision Tree have an accuracy 96.28% with predicition TIDAK true TIDAK is 362 and true YA is 14, and for the prediction YA true TIDAK is 15 and true YA is 34. 2. NAIVE BAYES (NB)   A Naive Bayes classifier is a simple probabilistic classifier based on applying Bayes’ theorem (from Bayesian statistics) with strong (naive) independence assumptions. A more descriptive term for the underlying probability model would be ‘independent feature...