What is the ratio of training and testing instances used in 10-fold cross validation (e.g: training 90% and testing 10percent) ?
It depends on kind of your sport. For canoe sprint testing ratio is 1/5 - 6 wk
K-fold cross-validation is done with 1/kth of your dataset as the test set while the rest is used for training but iterate through each k different dataset and average the classifier's errors. So your 90% for training and 10% for testing is correct.
what are the other types of classification errors while using machine learning such as False Positive or False Negative.?
05 June 2017 9,164 3 View
How dependent ensemble method (j48 with realadaboost) reduced classification errors during prediction?
04 May 2017 3,975 2 View
how to measure classification errors using weka. can we take the value of RSME or etc to utilize for taken the classification rate?
04 May 2017 4,095 7 View
Actually i am applying dependent ensemble which don't have multiple classifier. its only do ensemble a meta classifier like (realadaboost) with other one classifier like J48.. how they both work...
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if in a model i used a weak learner decision tree with an ensemble method adaboost for increasing accuracy. Q1: what will be called this model. Is it dependent ensemble model or other? Q2:How...
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03 April 2017 6,865 7 View
i want to make balance data usnig SMOTE in weka but there is no option for oversampling or undersampling.As per my knowledge SMOTE oversampling the minoroity class but when i apply it then it...
03 April 2017 3,061 1 View
kindly Confirm me the following steps of feature selection using weka. 1: open file and choose dataset. 2: click on select attribute 3: choose attribute evaluate and search method 4: selection of...
03 April 2017 3,063 13 View
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