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Update Cargo.toml (#299)

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* Update Cargo.toml

* chore: fix clippy

* chore: bump actions

* chore: fix clippy

* chore: update target name

---------

Co-authored-by: Luis Moreno <morenol@users.noreply.github.com>
This commit is contained in:
morenol
2025-04-24 23:24:29 -04:00
committed by GitHub
parent 4092e24c2a
commit 76d1ef610d
9 changed files with 17 additions and 33 deletions
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src/naive_bayes/bernoulli.rs
+1 -2
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@@ -257,8 +257,7 @@ impl<TY: Number + Ord + Unsigned> BernoulliNBDistribution<TY> {
/// Fits the distribution to a NxM matrix where N is number of samples and M is number of features.
/// * `x` - training data.
/// * `y` - vector with target values (classes) of length N.
/// * `priors` - Optional vector with prior probabilities of the classes. If not defined,
/// priors are adjusted according to the data.
/// * `priors` - Optional vector with prior probabilities of the classes. If not defined, priors are adjusted according to the data.
/// * `alpha` - Additive (Laplace/Lidstone) smoothing parameter.
/// * `binarize` - Threshold for binarizing.
fn fit<TX: Number + PartialOrd, X: Array2<TX>, Y: Array1<TY>>(
src/naive_bayes/gaussian.rs
+1 -2
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@@ -174,8 +174,7 @@ impl<TY: Number + Ord + Unsigned> GaussianNBDistribution<TY> {
/// Fits the distribution to a NxM matrix where N is number of samples and M is number of features.
/// * `x` - training data.
/// * `y` - vector with target values (classes) of length N.
/// * `priors` - Optional vector with prior probabilities of the classes. If not defined,
/// priors are adjusted according to the data.
/// * `priors` - Optional vector with prior probabilities of the classes. If not defined, priors are adjusted according to the data.
pub fn fit<TX: Number + RealNumber, X: Array2<TX>, Y: Array1<TY>>(
x: &X,
y: &Y,
src/naive_bayes/multinomial.rs
+1 -2
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@@ -207,8 +207,7 @@ impl<TY: Number + Ord + Unsigned> MultinomialNBDistribution<TY> {
/// Fits the distribution to a NxM matrix where N is number of samples and M is number of features.
/// * `x` - training data.
/// * `y` - vector with target values (classes) of length N.
/// * `priors` - Optional vector with prior probabilities of the classes. If not defined,
/// priors are adjusted according to the data.
/// * `priors` - Optional vector with prior probabilities of the classes. If not defined, priors are adjusted according to the data.
/// * `alpha` - Additive (Laplace/Lidstone) smoothing parameter.
pub fn fit<TX: Number + Unsigned, X: Array2<TX>, Y: Array1<TY>>(
x: &X,