View Source Scholar.Preprocessing.OrdinalEncoder (Scholar v0.3.0)
Implements encoder that converts integer value (substitute of categorical data in tensors) into other integer value.
The values assigned starts from 0 and go up to num_classes - 1.They are maintained in sorted manner.
This means that for x < y => encoded_value(x) < encoded_value(y).
Currently the module supports only 1D tensors.
Summary
Functions
Fit the ordinal encoder to provided data. The labels are assigned in a sorted manner.
Apply encoding on the provided tensor directly. It's equivalent to fit/2 and then transform/2 on the same data.
Encodes a tensor's values into integers from range 0 to :num_classes - 1 or -1 if the value did not occur in fitting process.
Functions
Fit the ordinal encoder to provided data. The labels are assigned in a sorted manner.
Options
:num_classes(pos_integer/0) - Required. Number of classes to be encoded.
Examples
iex> t = Nx.tensor([3, 2, 4, 56, 2, 4, 2])
iex> Scholar.Preprocessing.OrdinalEncoder.fit(t, num_classes: 4)
%Scholar.Preprocessing.OrdinalEncoder{
encoding_tensor: Nx.tensor(
[
[0, 2],
[1, 3],
[2, 4],
[3, 56]
]
)
}Apply encoding on the provided tensor directly. It's equivalent to fit/2 and then transform/2 on the same data.
Examples
iex> t = Nx.tensor([3, 2, 4, 56, 2, 4, 2])
iex> Scholar.Preprocessing.OridinalEncoder.fit_transform(t, num_classes: 4)
#Nx.Tensor<
s64[7]
[1, 0, 2, 3, 0, 2, 0]
>Encodes a tensor's values into integers from range 0 to :num_classes - 1 or -1 if the value did not occur in fitting process.
Examples
iex> t = Nx.tensor([3, 2, 4, 56, 2, 4, 2])
iex> enoder = Scholar.Preprocessing.OrdinalEncoder.fit(t, num_classes: 4)
iex> Scholar.Preprocessing.OrdinalEncoder.transform(enoder, t)
#Nx.Tensor<
s64[7]
[1, 0, 2, 3, 0, 2, 0]
>
iex> t = Nx.tensor([3, 2, 4, 56, 2, 4, 2])
iex> enoder = Scholar.Preprocessing.OrdinalEncoder.fit(t, num_classes: 4)
iex> new_tensor = Nx.tensor([2, 3, 4, 5, 4, 56, 2])
iex> Scholar.Preprocessing.OrdinalEncoder.transform(enoder, new_tensor)
#Nx.Tensor<
s64[7]
[0, 1, 2, -1, 2, 3, 0]
>