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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.
Prevalence : The measure of the number of people in a population who have a certain disease at a given point in time. It c an be measured by two methods, as point prevalence and p
Interim analyses : An analysis made before the planned end of a clinical trial, typically with the aim of detecting the treatment differences at the early stage and thus preventing
This term sometimes is applied to the model for explaining the differences found between naturally happening groups which are greater than those observed on some previous occasion;
Clinical trials : Medical experiments designed to assess which of two or more treatments is much more effective. It is based on one of the oldest philosophy of the scienti?c resear
Naor's distribution is the discrete probability distribution which arises from the following model; Assume an urn contains n balls of which one is red and the remainder is whit
how does it work exactly
Sam Tyler, a single taxpayer, social security number 111-44-1111, bought Rental Equipment on 04/01/2010. He paid $400,000 including all closing and delivery costs. In the current y
Maternal mortality : The maternal death is the death of a woman while pregnant, delivering a baby or within 42 days of the termination of pregnancy, from any reason related to or a
I do have a data of real gdp for each state and from 2000 to 2010 and I also have estimated population of illigel immigrants for each state from 2000 to 2010. In my thesis I am try
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
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