README
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Logistic Regression
Let's say that we have two classes, A and B, that we are trying to predict.
Let's also suppose that we are trying to predict A or B based on a variable x.
We need some function that goes to and stays at A for low values of x, and goes to and stays at B for higher values of x.
There is such a function. The function is called the logistic function, and it gives logistic regression its name.
It has the following form:
Plot this function
Documentation
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Index ¶
Examples ¶
Constants ¶
This section is empty.
Variables ¶
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Functions ¶
func TestTrainedData ¶
Example ¶
TestTrainedData(data.GetCleanLoanCSVData())
Output: Accuracy = 0.83
func TrainModel ¶
Example ¶
TrainModel(data.GetCleanLoanCSVData())
Output: p = 1 / ( 1 + exp(- m1 * FICO.score - m2) ) m1 = 13.65 m2 = -4.89
Types ¶
This section is empty.
Source Files
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