Improve the Classifier Accuracy for Continuous Attributes in Biomedical Datasets Using a New Discretization Method[J] . G. Madhu,T.V. Rajinikanth,A. Govardhan.Procedia Computer Science . 2014Madhu, G.; Rajinika
Hence if a decision tree is developed for any disease then accuracy is calculated that how much the decision is correct. Entropy (class): It is also called Shanon Entropy and is denoted by H(s) for a finite set S. It shows the evaluation of the amount of unpredictability in data. Here...
classifier n. 1. 分类成分,分类词(能显示同义所属关系,如前缀 un 是表示反义的分类成分)an affix or word which shows that a word belongs to a group of words with similar meanings. For example the prefix ‘un’ is a classifier that shows the word is negative. ...
Bacardit, J., Butz, M.V.: Data mining in learning classifier systems: comparing xcs with gassist. In: Advances at the frontier of Learning Classifier Systems. Springer, Berlin Heidelberg New York (2007) 282–290 Google Scholar Wilson, S.W.: Classifier fitness based on accuracy. Evolutionar...
Beigy, "Using a classifier pool in accuracy based tracking of recurring concepts in data stream classifica- tion," Evolving Systems, vol. 4, no. 1, pp. 43-60, 2013.M. J. Hosseini, Z. Ahmadi, and H. Beigy, "Using a classifier pool in accuracy based tracking of recurring concepts ...
However, the accuracy for plasma cells was lower since around 20% of these were annotated as non-immune cells. The classification accuracy of CD4+ and CD8+ T cells was in the range of 82% and 98%. Notably, around 30,000 NK cells showed more than 96% accuracy across three independent ...
Matthew’s Correlation Coefficient (MCC) is another measure of binary classification performance34that has been extended to handle multi-class problems35. Its main merit is in taking into account true negatives (accuracy or\({F}_{1}\)do not), which makes MCC especially useful when negative exa...
#RULECOUNT: 4 the number of rules in the model #TIMEms: 19 the time for training the model (ms) #MEMORYmb: 1.9 the memory used for training the model (MB)=== CLASSIFICATION RESULTS ON TRAINING DATA === #NAME: CBA #ACCURACY: 0.7778 accuracy of the model on training data #RECALL:...
A previous blog post, The Basics of Classifier Evaluation, Part 1, made the point that classifiers shouldn’t use classification accuracy — that is, the portion of labels predicted correctly — as a performance metric. There are several good reasons for avoiding accuracy, having to do with cla...
it is critical in these applications to have a classifier that scales well and can handle training data of this magnitude. As an additional advantage, being able to classify large training data also leads to an improvement in the classification accuracy. Such a result was demonstrated, for exampl...