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Patch to version 0.4.0 (#257)

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* uncomment test

* Add random test for logistic regression

* linting

* Bump version

* Add test for logistic regression

* linting

* initial commit

* final

* final-clean

* Bump to 0.4.0

* Fix linter

* cleanup

* Update CHANDELOG with breaking changes

* Update CHANDELOG date

* Add functional methods to DenseMatrix implementation

* linting

* add type declaration in test

* Fix Wasm tests failing

* linting

* fix tests

* linting

* Add type annotations on BBDTree constructor

* fix clippy

* fix clippy

* fix tests

* bump version

* run fmt. fix changelog

---------

Co-authored-by: Edmund Cape <edmund@Edmunds-MacBook-Pro.local>
This commit is contained in:
Lorenzo
2024-03-04 13:51:27 +00:00
committed by GitHub
parent 80a93c1a0e
commit 239c00428f
45 changed files with 759 additions and 406 deletions
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src/naive_bayes/multinomial.rs
+9 -6
View File
@@ -20,13 +20,13 @@
//! &[0, 2, 0, 0, 1, 0],
//! &[0, 1, 0, 1, 0, 0],
//! &[0, 1, 1, 0, 0, 1],
//! ]);
//! ]).unwrap();
//! let y: Vec<u32> = vec![0, 0, 0, 1];
//! let nb = MultinomialNB::fit(&x, &y, Default::default()).unwrap();
//!
//! // Testing data point is:
//! // Chinese Chinese Chinese Tokyo Japan
//! let x_test = DenseMatrix::from_2d_array(&[&[0, 3, 1, 0, 0, 1]]);
//! let x_test = DenseMatrix::from_2d_array(&[&[0, 3, 1, 0, 0, 1]]).unwrap();
//! let y_hat = nb.predict(&x_test).unwrap();
//! ```
//!
@@ -433,7 +433,8 @@ mod tests {
&[0, 2, 0, 0, 1, 0],
&[0, 1, 0, 1, 0, 0],
&[0, 1, 1, 0, 0, 1],
]);
])
.unwrap();
let y: Vec<u32> = vec![0, 0, 0, 1];
let mnb = MultinomialNB::fit(&x, &y, Default::default()).unwrap();
@@ -467,7 +468,7 @@ mod tests {
// Testing data point is:
// Chinese Chinese Chinese Tokyo Japan
let x_test = DenseMatrix::<u32>::from_2d_array(&[&[0, 3, 1, 0, 0, 1]]);
let x_test = DenseMatrix::<u32>::from_2d_array(&[&[0, 3, 1, 0, 0, 1]]).unwrap();
let y_hat = mnb.predict(&x_test).unwrap();
assert_eq!(y_hat, &[0]);
@@ -495,7 +496,8 @@ mod tests {
&[2, 0, 3, 3, 1, 2, 0, 2, 4, 1],
&[2, 4, 0, 4, 2, 4, 1, 3, 1, 4],
&[0, 2, 2, 3, 4, 0, 4, 4, 4, 4],
]);
])
.unwrap();
let y: Vec<u32> = vec![2, 2, 0, 0, 0, 2, 1, 1, 0, 1, 0, 0, 2, 0, 2];
let nb = MultinomialNB::fit(&x, &y, Default::default()).unwrap();
@@ -554,7 +556,8 @@ mod tests {
&[0, 1, 0, 0, 1, 0],
&[0, 1, 0, 1, 0, 0],
&[0, 1, 1, 0, 0, 1],
]);
])
.unwrap();
let y = vec![0, 0, 0, 1];
let mnb = MultinomialNB::fit(&x, &y, Default::default()).unwrap();