Content based filtering

Bayes Classifier

Background knowledge:

By comparing values of $P(c(\bar{X})=1|x_1,...,x_d)$ and $P(c(\bar{X})=-1|x_1,...,x_d)$ , one can determine whether or not the active user likes $\bar{X}$ . To predict $P(c(\bar{X})=1)$ , the following expression is used.

P(c(\bar{X})=1)=\dfrac{|D_L^+|+\alpha}{|D_L|+2\cdot \alpha}

In this expression, $$

f(x) = x * e^{2 pi i \xi x}

PreviousSummary NextEnsemble-Based

Last updated 3 years ago

Was this helpful?

Bayes Classifier

Background knowledge:

By comparing values of

P(c(\bar{X})=1|x_1,...,x_d)

and

P(c(\bar{X})=-1|x_1,...,x_d)

, one can determine whether or not the active user likes

\bar{X}

. To predict

P(c(\bar{X})=1)

, the following expression is used.

P(c(\bar{X})=1)=\dfrac{|D_L^+|+\alpha}{|D_L|+2\cdot \alpha}

In this expression, $$

f(x) = x * e^{2 pi i \xi x}