Econlearn documentation

Supervised learning (Regression)

TilecodeRegressor(D, T, L[, mem_max, ...]) Tile coding for function approximation (Supervised Learning).

Unsupervised learning

TilecodeSamplegrid(D, L[, mem_max, cores, ...]) Construct a sample grid (sample of approximately equidistant points) from
TilecodeDensity(D, T, L[, mem_max, offset, ...]) Tile coding approximation of the pdf of X Fits by averaging.
TilecodeNearestNeighbour(D, L[, mem_max, ...]) Fast approximate nearest neighbour search using tile coding data structure

Reinforcement learning

TilecodeQVIteration(D, T, L, radius, beta[, ...]) Solve a MDP with 1 policy variable and D state variables by Q-V Iteration