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notes:bayesian_classification

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 notes:bayesian_classification [2013/03/15 14:11]andy [Combining words] notes:bayesian_classification [2013/03/15 14:13]andy Both sides previous revision Previous revision 2013/03/15 14:13 andy 2013/03/15 14:11 andy [Combining words] 2013/03/15 14:06 andy [Combining words] 2013/03/15 13:37 andy [Combining words] 2013/03/15 13:36 andy [Combining words] 2013/03/15 13:12 andy [Combining words] 2013/03/15 12:18 andy 2013/03/15 11:43 andy [Combining words] 2013/03/15 10:29 andy [Classification based on a word] 2013/03/14 16:33 andy [Combining words] 2013/03/14 16:16 andy 2013/03/14 15:21 andy 2013/03/14 11:56 andy created 2013/03/15 14:13 andy 2013/03/15 14:11 andy [Combining words] 2013/03/15 14:06 andy [Combining words] 2013/03/15 13:37 andy [Combining words] 2013/03/15 13:36 andy [Combining words] 2013/03/15 13:12 andy [Combining words] 2013/03/15 12:18 andy 2013/03/15 11:43 andy [Combining words] 2013/03/15 10:29 andy [Classification based on a word] 2013/03/14 16:33 andy [Combining words] 2013/03/14 16:16 andy 2013/03/14 15:21 andy 2013/03/14 11:56 andy created Line 96: Line 96: $$\Rightarrow P(C_i|W_a \cap W_b \cap ... \cap W_z) = \frac{\prod\limits_{j=a}^z{N_{C_i}(W_j)}}{N_{C_i}^{x-1}\sum\limits_{k=1}^n{\frac{1}{N_{C_k}^{x-1}}\prod\limits_{j=a}^z{N_{C_k}(W_j)}}}$$ $$\Rightarrow P(C_i|W_a \cap W_b \cap ... \cap W_z) = \frac{\prod\limits_{j=a}^z{N_{C_i}(W_j)}}{N_{C_i}^{x-1}\sum\limits_{k=1}^n{\frac{1}{N_{C_k}^{x-1}}\prod\limits_{j=a}^z{N_{C_k}(W_j)}}}$$ - Where $x$ is the total number of words. This version may help avoid underflow, but may instead be susceptible to overflow due to the exponentiation involved. + Where $x$ is the total number of words. This version may help avoid underflow, but may instead be susceptible to overflow due to the exponentiation involved. ​As a result, it may be preferable to move the divisions back inside the iterations. ==== Two-category case ==== ==== Two-category case ====
notes/bayesian_classification.txt · Last modified: 2013/03/15 14:13 by andy