diff --git a/md/Random-Forest.md b/md/Random-Forest.md new file mode 100644 index 0000000..32b05a4 --- /dev/null +++ b/md/Random-Forest.md @@ -0,0 +1,23 @@ +# Random Forest + +__function__ RANDOMFOREST( S,F ) __return__ solution: +  __input__ S --> training set consisting of (Xi,Yi) +   F --> No. of features +   H <-- null + +  for __each__ i 1,..B(no.of trees) __do__ +    h(i) --> RANDOMISEDTREE( S(i),F ) +    H <-- H U {h(i)} +    __return__ H + +__function__ RANDOMISEDTREE(S,F) __return__ learnt_tree : + +  for each node of the tree do +    f <-- Randomised subset of F +    Split and choose best feature in f + + + + + +