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StatsToDo : Classification by Basic Bayes Probability Program

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Related link :
Classification by Bayes Probability Explained Page
Classification by Naive Bayes Probability Program Page

Program Help & Hints
Data: Attributes ± Outcome Designation
Data Input for Analysis of reference Data
    The data is for a table with 2 columns
    Each row contains data from a case from the reference data
    Col 1 = Series of + (Positive) and - (Negative) for attributes
    Col 2 = Single character or word for Outcome Designation

Data Input for Interpretation
    The data is for a table with single columns
    Each row contains data from a case from the input data for interpretation
    Column with series of + (Positive) and - (Negative) for attributes

Program 1.

Reference Table of Counts
Input Table of Counts for Analysis of reference Table
    This is an alternative input for analysis
    The table is a count of the reference data
    Col 1 contains attribute clusters
    The other columns are the outcomes
    The first row contains the outcome names
    Each following row represent a set of attributes
    Each cell is the count of the attribute (row) for that outcome (Col)
Program 2.

Probabilities for each pattern given the outcome P(p|o)
Table of Probabilities

Array of of Apriori Probabilities

Array of Costs Coefficients

Input Table of Probability of attributes for each outcome P(p|o)
    This is a table of probabilities P(p|o)
    Col 1 contains attribute patternss
    The other columns are the outcomes
    The first row contains the outcome names
    Each following row shows each attribute pattern, and its P(p|o)
    Each cell is the Probability pattern for the outcome P(p|o)

Array of Apriori Probabilities
    Probability for each outcome before attributes patterns are known
    Single row, number of columns = number of outcomes
    Columns separated by spaces of tabs
    Values representing relative probabilities

Array of Costs
    Cost of wrongly missing an outcome
    Single row, number of columns = number of outcomes
    Columns separated by spaces of tabs
    Values representing relative costs

Program 3.

Program 4.