Estimates the piece value coefficient by different linear regression models given a data of chess piece values with results.
- Install python
- Install sklearn
- pip install sklearn
- Install pandas
- pip install pandas
fen P-p ... Q-q result
0 r3r3/pbp1kp2/2p2bpp/2N1p3/8/5B2/PPP2PPP/2KRR3 ... -1 ... 0 1
1 3rr1k1/pb4pp/2p1n3/1p1n4/1P1qN3/P7/B1Q2PPP/3R1... 0 ... 0 0
2 6k1/p1p3p1/1p5p/4p3/2P2n2/2P2B2/P4P1P/6K1 w - - -1 ... 0 0
3 6k1/6p1/2p5/p1q4p/2P1n3/p4RNP/R5P1/7K b - - -2 ... -1 0
4 4rk2/1R5p/6p1/r2P1p2/p1PpB3/5P2/P5PP/4K2R w K - 1 ... 0 1
... ... ... ... ... ...
1206278 8/pp6/2pk4/5R2/1P6/r7/5PK1/8 w - - -1 ... 0 0
1206279 1r6/8/8/8/R6p/6nk/5K2/8 w - - -1 ... 0 0
1206280 7R/6p1/6k1/4Kp2/6rP/8/8/8 w - - -1 ... 0 0
1206281 1r2k3/1q3p1p/p3pQ2/8/2pR4/5Pr1/1PP3P1/R6K b - - -1 ... 0 1
1206282 8/8/8/4p1p1/1K1kP1P1/5P2/8/8 b - - 1 ... 0 0
[1206283 rows x 7 columns]
Features that are not 0:
=======================
piece: P-p, num: 579322, pct: 48.03%
piece: N-n, num: 254340, pct: 21.08%
piece: B-b, num: 251468, pct: 20.85%
piece: R-r, num: 117705, pct: 9.76%
piece: Q-q, num: 24378, pct: 2.02%
model 1: Linear Regression
=======================
Metrics:
mse: 0.16410313874489252
mae: 0.3518987466042799
r2_score: 0.3396676182349635
coefficients: [0.17450496 0.33598911 0.37350445 0.52490821 0.96500647]
pawn: 175, knight: 336, bishop: 374, rook: 525, queen: 965
model 2: Ridge
=======================
Metrics:
mse: 0.16410313539039326
mae: 0.35189949045291846
r2_score: 0.33966763173308734
coefficients: [0.1745041 0.33597642 0.37349147 0.5248878 0.96495136]
pawn: 175, knight: 336, bishop: 373, rook: 525, queen: 965
model 3: Lasso
=======================
Metrics:
mse: 0.16410447794342517
mae: 0.35203124553077647
r2_score: 0.33966222945225355
coefficients: [0.17432736 0.33381853 0.37129856 0.52166285 0.95753882]
pawn: 174, knight: 334, bishop: 371, rook: 522, queen: 958
model 4: Stochastic Gradient Descent
=======================
Metrics:
mse: 0.16415350143193788
mae: 0.35034513471558837
r2_score: 0.3394649645054669
coefficients: [0.17870765 0.33873901 0.37098609 0.53000329 0.96326733]
pawn: 179, knight: 339, bishop: 371, rook: 530, queen: 963
References:
mse : mean squared error
mae : mean absolute error
r2_score : coefficient of determination