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The non-trivial extraction of implicit, earlier unknown and potentially useful information from data, specifically high-dimensional data, using pattern recognition, artificial intelligence and machine learning, and presentation of the information extracted in a form that is without difficulty understandable to humans. Significant biological discoveries are now frequently made by combining data mining methods with the traditional laboratory techniques; an instance is the discovery of novel regulatory areas for heat shock genes in C. Elegans made by mining vast amounts of the gene expression and sequence data for the significant patterns.
R-squared is regarded as the coefficient of determination and is used to give the proportion of the fluctuation of the variance of one variable to another variable. R-squared also
What is statistical inference? Statistical inference can be defined as the method of drawing conclusions from data which are subject to random variations. This is based o
Historical controls : The group of patients treated in the past with the standard therapy, taken in use as the control group for evaluating the new treatment on the present patient
hello I have a dataset including both categorical & numerical variable for market segmentation.how can i cluster them via k-means in matlab? thank you
I have a problem I am trying to solve. An oil company thinks that there is a 60% chance that there is oil in the land they own. Before drilling they run a soil test. When there is
The Null Hypothesis - H0: β 1 = 0 i.e. there is homoscedasticity errors and no heteroscedasticity exists The Alternative Hypothesis - H1: β 1 ≠ 0 i.e. there is no homoscedasti
Incidental parameter problem is a problem which sometimes occurs when the number of parameters increases in the tandem with the number of observations. For instance, models for pa
Relative risk is the measure of the association between the exposure to a particular factor and the risk or probability of a convinced outcome, calculated as follows therefor
Kaiser's rule is the rule frequently used in the principal components analysis for selecting the suitable the number of components. When the components are derived from correlati
Multiple imputation : The Monte Carlo technique in which missing values in the data set are replaced by m> 1 simulated versions, where m is usually small (say 3-10). Each of simula
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