How could we do predictions with data mining for quant development?
Predictive models can be grouped in two major groups: classification and regression models.
Both aim at building models that predicts the value of a variable knowing the values of other variables. Both models accept in input a set of training data. Each training instance has several attributes, one of which is the variable to be predicted. In classification, this variable is categorical and it is called class variable, in regression the variable is real–valued and is known as dependent variable. etc. Predictive models learn, using the
training data at hand, a mapping from the input variables to the dependent variable. The resulting model is then used to predict the value of the dependent variable for a new instance of which all the independent variables are known.
Examples of classification algorithms are: decision trees, neural network, nearest neighbor, rule-learners, etc..
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