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 |