ML algorithm which produces an output of variable length
$begingroup$
I am trying to solve the following problem:
Let's say I have a chess position:
I encode each square as one-hot encoded vector of length 13
- index 0 for empty square
- index 1 for white pawn
- index 2 for black pawn
- index 3 for white bishop
- index 4 for black bishop
- etc..
So, at the end I have a matrix ${M}$ with a shape 64x13, which I intend to use as an input of the model. I want to create a model able to map matrix ${M}$ to FEN representation of the position.
Given the example above, FEN representation of the position is: 1b1N4/7k/4b3/8/8/8/3P4/3K4
The length of a FEN-string is not fixed. What machine learning alghorythm can I use in that case ?
P.S. I realize that it is trivial to just write a function to map ${M}$ to FEN, but I do not want it, I want the model to learn it from data.
machine-learning algorithms
asked 7 mins ago
koryakinpkoryakinp
44110
$endgroup$
add a comment |
$begingroup$
I am trying to solve the following problem:
Let's say I have a chess position:
I encode each square as one-hot encoded vector of length 13
- index 0 for empty square
- index 1 for white pawn
- index 2 for black pawn
- index 3 for white bishop
- index 4 for black bishop
- etc..
So, at the end I have a matrix ${M}$ with a shape 64x13, which I intend to use as an input of the model. I want to create a model able to map matrix ${M}$ to FEN representation of the position.
Given the example above, FEN representation of the position is: 1b1N4/7k/4b3/8/8/8/3P4/3K4
The length of a FEN-string is not fixed. What machine learning alghorythm can I use in that case ?
P.S. I realize that it is trivial to just write a function to map ${M}$ to FEN, but I do not want it, I want the model to learn it from data.
machine-learning algorithms
asked 7 mins ago
koryakinpkoryakinp
44110
$endgroup$
add a comment |
$begingroup$
I am trying to solve the following problem:
Let's say I have a chess position:
I encode each square as one-hot encoded vector of length 13
- index 0 for empty square
- index 1 for white pawn
- index 2 for black pawn
- index 3 for white bishop
- index 4 for black bishop
- etc..
So, at the end I have a matrix ${M}$ with a shape 64x13, which I intend to use as an input of the model. I want to create a model able to map matrix ${M}$ to FEN representation of the position.
Given the example above, FEN representation of the position is: 1b1N4/7k/4b3/8/8/8/3P4/3K4
The length of a FEN-string is not fixed. What machine learning alghorythm can I use in that case ?
P.S. I realize that it is trivial to just write a function to map ${M}$ to FEN, but I do not want it, I want the model to learn it from data.
machine-learning algorithms
asked 7 mins ago
koryakinpkoryakinp
44110
$endgroup$
I am trying to solve the following problem:
Let's say I have a chess position:
I encode each square as one-hot encoded vector of length 13
- index 0 for empty square
- index 1 for white pawn
- index 2 for black pawn
- index 3 for white bishop
- index 4 for black bishop
- etc..
So, at the end I have a matrix ${M}$ with a shape 64x13, which I intend to use as an input of the model. I want to create a model able to map matrix ${M}$ to FEN representation of the position.
Given the example above, FEN representation of the position is: 1b1N4/7k/4b3/8/8/8/3P4/3K4
The length of a FEN-string is not fixed. What machine learning alghorythm can I use in that case ?
P.S. I realize that it is trivial to just write a function to map ${M}$ to FEN, but I do not want it, I want the model to learn it from data.
machine-learning algorithms
machine-learning algorithms
asked 7 mins ago
koryakinpkoryakinp
44110
asked 7 mins ago
koryakinpkoryakinp
44110
asked 7 mins ago
koryakinpkoryakinp
44110
asked 7 mins ago
koryakinpkoryakinp
44110
asked 7 mins ago
koryakinpkoryakinp
44110
44110
add a comment |
add a comment |
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