\documentclass[11pt]{amsart}
\usepackage{ulem}
\usepackage{algorithmic}

\begin{document}

\section{BORE (Best OR Rest)}

\begin{algorithmic}
\STATE LET Data = \{Instances\} 
\STATE LET Attributes = \{Column-wise attributes\}
\STATE LET Best = \{Instances $\in$ Data of the best class\}
\STATE LET Rest = \{Instances $\in$ Data of all other classes\}
\FOR {A $\in$ Attributes}
    \FOR {bin $\in$ A}
    	\STATE Prob\_BEST = $|Best|$ / $|Data|$
    	\STATE Prob\_REST = $|Rest|$ / $|Data|$
    	\STATE FREQ($bin|Best$) = $|$ $\{ bin | bin \in  Best_A\}$ $|$ / $|Best|$
    	\STATE FREQ($bin|Rest$) = $|$ $\{ bin | bin \in Rest_A \}$ $|$ / $|Rest|$
    	\STATE LIKE($Best|bin$) = $FREQ(bin|Best) * Prob\_Best$
    	\STATE LIKE($Rest|bin$) = $FREQ(bin|Rest) * Prob\_Rest$
   		\STATE LIKE\_BEST\_REST = LIKE($Best|bin$) + LIKE($Rest|bin$)
   		\STATE RANK = LIKE$(Best|bin)^2$ / LIKE\_BEST\_REST
    \ENDFOR
\ENDFOR
\end{algorithmic}


\section{Cliff}
\begin{algorithmic}
\STATE LET Data = \{Instances\}
\STATE LET Criterias = \{Highest ranked value,attribute sets for each class obtained from BORE\}
\STATE LET Prototypes = \{\}

\FOR { value,attributes $\in$ Criterias }
	\STATE Prototypes = Prototypes $\cup$ $ \{ instances | instances \in data, value \in instance_{attributes}\}$
\ENDFOR

\end{algorithmic}

\section{Midpoint Sampling}
\begin{algorithmic}
\STATE Pick a point $P_1$ randomly from training set.
\STATE Pick the closest point $P_2$ in the training set belonging to the opposite class.
\STATE Find the midpoint $M$ between $P_1$ and $P_2$.
\STATE Request a classification for the closest unlabeled point to point $M$.
\end{algorithmic}

\end{document}