docs update

docs/examples/classification.md

@@ -0,0 +1,62 @@
+# Classification
+
+This example demonstrates how use Classification module from the `mambular` package.
+
+```python
+import numpy as np
+import pandas as pd
+from sklearn.model_selection import train_test_split
+from mambular.models import MambularClassifier
+# Set random seed for reproducibility
+np.random.seed(0)
+```
+
+Let's generate some random data to use for classification.
+
+```python
+# Number of samples
+n_samples = 1000
+n_features = 5
+```
+
+Generate random features
+
+```python
+X = np.random.randn(n_samples, n_features)
+coefficients = np.random.randn(n_features)
+```
+
+Generate target variable
+
+```python
+y = np.dot(X, coefficients) + np.random.randn(n_samples)
+## Convert y to multiclass by categorizing into quartiles
+y = pd.qcut(y, 4, labels=False)
+```
+
+Create a DataFrame to store the data
+
+```python
+data = pd.DataFrame(X, columns=[f"feature_{i}" for i in range(n_features)])
+data["target"] = y
+```
+
+Split data into features and target variable
+```python
+X = data.drop(columns=["target"])
+y = data["target"].values
+
+X_train, X_test, y_train, y_test = train_test_split(
+    X, y, test_size=0.2, random_state=42
+)
+```
+
+Instantiate the classifier and fit the model on training data
+```python
+classifier = MambularClassifier()
+
+# Fit the model on training data
+classifier.fit(X_train, y_train, max_epochs=10)
+
+print(classifier.evaluate(X_test, y_test))
+```

docs/examples/distributional.rst

@@ -1,7 +1,7 @@
 .. _dist_example:
 
-Distributional Example
-======================
+Distributional
+==============
 
 This example demonstrates how use Distributional from the `mambular` package.
 

docs/examples/embedding.rst

@@ -1,7 +1,7 @@
 .. _embedding_example:
 
-Embedding Example
-=================
+Embedding
+=========
 
 This example demonstrates how use Embedding from the `mambular` package.
 

docs/examples/regression.rst

@@ -1,7 +1,7 @@
 .. _regression_example:
 
-Regression Example
-==================
+Regression
+==========
 
 This example demonstrates how use Regression module from the `mambular` package.
 

docs/index.rst

@@ -27,11 +27,12 @@
 .. toctree::
    :name: API Reference
    :caption: API Reference
-   :maxdepth: 1
+   :maxdepth: 2
+   :hidden:
 
-   api/models/index
-   api/base_models/index
-   api/utils/index
+   api/models/Models
+   api/base_models/BaseModels
+   api/utils/Preprocessor
 
 
 .. toctree::