Revert "Merge branch 'main' into fix-doc-conflict"

This reverts commit 707d664, reversing
changes made to 020e102.

docs/SUMMARY.md

@@ -89,6 +89,10 @@
     * [nn.softsign](framework/operators/neural-network/nn.softsign.md)
     * [nn.softplus](framework/operators/neural-network/nn.softplus.md)
     * [nn.linear](framework/operators/neural-network/nn.linear.md)
+  * [Machine Learning](framework/operators/machine-learning/README.md)
+    * [Tree Regressor](framework/operators/machine-learning/tree-regressor/README.md)
+      * [tree.fit](framework/operators/machine-learning/tree-regressor/tree.fit.md)
+      * [tree.predict](framework/operators/machine-learning/tree-regressor/tree.predict.md)
 
 ## 🏛 Hub
 

docs/framework/operators/machine-learning/README.md

@@ -0,0 +1,2 @@
+# Machine Learning
+

docs/framework/operators/machine-learning/tree-regressor/README.md

@@ -0,0 +1,22 @@
+# Tree Regressor
+
+`TreeRegressorTrait` provides a trait definition for decision tree regression. This trait offers functionalities to build a decision tree and predict target values based on input features.
+
+```rust
+use orion::operators::ml::TreeRegressorTrait;
+```
+
+### Data types
+
+Orion supports currently only fixed point data types for `TreeRegressorTrait`.
+
+| Data type            | dtype                                                         |
+| -------------------- | ------------------------------------------------------------- |
+| Fixed point (signed) | `TreeRegressorTrait<FP8x23 \| FP16x16 \| FP64x64 \| FP32x32>` |
+
+***
+
+| function | description |
+| --- | --- |
+| [`tree.fit`](tree.fit.md) | Constructs a decision tree regressor based on the provided data and target values. |
+| [`tree.predict`](tree.predict.md) | Given a set of features, predicts the target value using the constructed decision tree. |

docs/framework/operators/machine-learning/tree-regressor/tree.fit.md

@@ -0,0 +1,50 @@
+# TreeRegressorTrait::fit
+
+```rust 
+   fn fit(data: Span<Span<T>>, target: Span<T>, max_depth: usize, random_state: usize) -> TreeNode<T>;
+```
+
+Builds a decision tree based on the provided data and target values up to a specified maximum depth.
+
+## Args
+
+* `data`: A span of spans representing rows of features in the dataset.
+* `target`: A span representing the target values corresponding to each row in the dataset.
+* `max_depth`: The maximum depth of the decision tree. The tree stops growing once this depth is reached.
+* `random_state`: It ensures that the tie-breaking is consistent across multiple runs, leading to reproducible results.
+
+## Returns
+
+A `TreeNode` representing the root of the constructed decision tree.
+
+## Type Constraints
+
+Constrain input and output types to fixed point tensors.
+
+## Examples
+
+```rust
+use orion::operators::ml::{FP16x16TreeRegressor, TreeRegressorTrait};
+use orion::numbers::{FP16x16, FixedTrait};
+
+fn tree_regressor_example() {
+
+ let data = array![
+     array![FixedTrait::new_unscaled(1, false), FixedTrait::new_unscaled(2, false)].span(),
+     array![FixedTrait::new_unscaled(3, false), FixedTrait::new_unscaled(4, false)].span(),
+     array![FixedTrait::new_unscaled(5, false), FixedTrait::new_unscaled(6, false)].span(),
+     array![FixedTrait::new_unscaled(7, false), FixedTrait::new_unscaled(8, false)].span(),
+ ]
+     .span();
+
+ let target = array![
+     FixedTrait::new_unscaled(2, false),
+     FixedTrait::new_unscaled(4, false),
+     FixedTrait::new_unscaled(6, false),
+     FixedTrait::new_unscaled(8, false)
+ ]
+     .span();
+
+ TreeRegressorTrait::fit(data, target, 3, 42);
+}
+```

docs/framework/operators/machine-learning/tree-regressor/tree.predict.md

@@ -0,0 +1,53 @@
+# tree.predict
+
+```rust
+   fn predict(ref self: TreeNode<T>, features: Span<T>) -> T;
+```
+
+Predicts the target value for a set of features using the provided decision tree.
+
+## Args
+
+* `self`: A reference to the decision tree used for making the prediction.
+* `features`: A span representing the features for which the prediction is to be made.
+
+## Returns
+
+The predicted target value.
+
+## Type Constraints
+
+Constrain input and output types to fixed point tensors.
+
+## Examples
+
+```rust
+use orion::operators::ml::{FP16x16TreeRegressor, TreeRegressorTrait};
+use orion::numbers::{FP16x16, FixedTrait};
+
+fn tree_regressor_example() {
+
+ let data = array![
+     array![FixedTrait::new_unscaled(1, false), FixedTrait::new_unscaled(2, false)].span(),
+     array![FixedTrait::new_unscaled(3, false), FixedTrait::new_unscaled(4, false)].span(),
+     array![FixedTrait::new_unscaled(5, false), FixedTrait::new_unscaled(6, false)].span(),
+     array![FixedTrait::new_unscaled(7, false), FixedTrait::new_unscaled(8, false)].span(),
+ ]
+     .span();
+
+ let target = array![
+     FixedTrait::new_unscaled(2, false),
+     FixedTrait::new_unscaled(4, false),
+     FixedTrait::new_unscaled(6, false),
+     FixedTrait::new_unscaled(8, false)
+ ]
+     .span();
+
+ let mut tree = TreeRegressorTrait::fit(data, target, 3);
+
+ let prediction_1 = tree
+   .predict(
+       array![FixedTrait::new_unscaled(1, false), FixedTrait::new_unscaled(2, false),].span()
+   );
+}
+```