Fix broken ML files, resolve FIXME issues, and add new algorithms

- Fix 4 broken machine learning files using deprecated sklearn functions
  - Replace plot_confusion_matrix with ConfusionMatrixDisplay.from_estimator
  - Replace load_boston with fetch_california_housing dataset
  - Add proper type hints and comprehensive doctests

- Fix FIXME issues in bipartite graph checker
  - Add input validation for invalid graph structures
  - Raise ValueError for disconnected nodes
  - Update type hints to support generic hashable types
  - Fix filename typo: check_bipatrite.py -> check_bipartite.py

- Add new algorithms with educational value
  - Trie-based autocomplete system with frequency ranking
  - B-Tree implementation for database-like operations
  - Rabin-Karp string search with multiple pattern support

All new code includes comprehensive doctests and follows project guidelines.

Author: M-H-Jishan

data_structures/binary_tree/b_tree.py

@@ -0,0 +1,278 @@
+"""
+B-Tree Implementation
+
+A B-Tree is a self-balancing tree data structure that maintains sorted data and allows
+searches, sequential access, insertions, and deletions in logarithmic time.
+
+B-Trees are commonly used in databases and file systems.
+
+Reference: https://en.wikipedia.org/wiki/B-tree
+Time Complexity:
+    - Search: O(log n)
+    - Insert: O(log n)
+    - Delete: O(log n)
+"""
+
+from __future__ import annotations
+
+
+class BTreeNode:
+    """
+    A node in the B-Tree.
+
+    Attributes:
+        keys: List of keys stored in the node
+        children: List of child nodes
+        is_leaf: Boolean indicating if this is a leaf node
+    """
+
+    def __init__(self, is_leaf: bool = True) -> None:
+        self.keys: list[int] = []
+        self.children: list[BTreeNode] = []
+        self.is_leaf = is_leaf
+
+    def split(self, parent: BTreeNode, index: int) -> None:
+        """
+        Split this node and move the median key up to the parent.
+
+        Args:
+            parent: The parent node
+            index: The index in parent's children where this node is located
+        """
+        new_node = BTreeNode(is_leaf=self.is_leaf)
+        mid_index = len(self.keys) // 2
+        new_node.keys = self.keys[mid_index + 1 :]
+        self.keys = self.keys[:mid_index]
+
+        if not self.is_leaf:
+            new_node.children = self.children[mid_index + 1 :]
+            self.children = self.children[: mid_index + 1]
+
+        parent.keys.insert(index, self.keys[mid_index])
+        parent.children.insert(index + 1, new_node)
+
+
+class BTree:
+    """
+    B-Tree data structure.
+
+    A B-Tree of order m has the following properties:
+    - Every node has at most m children
+    - Every non-leaf node (except root) has at least ⌈m/2⌉ children
+    - The root has at least 2 children if it is not a leaf
+    - All leaves appear on the same level
+    - A non-leaf node with k children contains k−1 keys
+
+    Examples:
+    >>> btree = BTree(order=3)
+    >>> btree.insert(10)
+    >>> btree.insert(20)
+    >>> btree.insert(5)
+    >>> btree.insert(6)
+    >>> btree.insert(12)
+    >>> btree.insert(30)
+    >>> btree.insert(7)
+    >>> btree.insert(17)
+    >>> btree.search(6)
+    True
+    >>> btree.search(15)
+    False
+    >>> btree.search(12)
+    True
+    >>> btree.search(100)
+    False
+    """
+
+    def __init__(self, order: int = 3) -> None:
+        """
+        Initialize a B-Tree.
+
+        Args:
+            order: The maximum number of children a node can have (must be >= 3)
+
+        Raises:
+            ValueError: If order is less than 3
+        """
+        if order < 3:
+            msg = "Order must be at least 3"
+            raise ValueError(msg)
+
+        self.order = order
+        self.min_keys = (order + 1) // 2 - 1
+        self.max_keys = order - 1
+        self.root = BTreeNode()
+
+    def search(self, key: int, node: BTreeNode | None = None) -> bool:
+        """
+        Search for a key in the B-Tree.
+
+        Args:
+            key: The key to search for
+            node: The node to start searching from (defaults to root)
+
+        Returns:
+            True if the key exists, False otherwise
+
+        Time Complexity: O(log n)
+
+        >>> btree = BTree(order=3)
+        >>> btree.insert(50)
+        >>> btree.search(50)
+        True
+        >>> btree.search(25)
+        False
+        """
+        if node is None:
+            node = self.root
+
+        i = 0
+        while i < len(node.keys) and key > node.keys[i]:
+            i += 1
+
+        if i < len(node.keys) and key == node.keys[i]:
+            return True
+
+        if node.is_leaf:
+            return False
+
+        return self.search(key, node.children[i])
+
+    def insert(self, key: int) -> None:
+        """
+        Insert a key into the B-Tree.
+
+        Args:
+            key: The key to insert
+
+        Time Complexity: O(log n)
+
+        >>> btree = BTree(order=3)
+        >>> btree.insert(10)
+        >>> btree.insert(20)
+        >>> btree.insert(30)
+        >>> btree.search(20)
+        True
+        """
+        if len(self.root.keys) >= self.max_keys:
+            new_root = BTreeNode(is_leaf=False)
+            new_root.children.append(self.root)
+            self.root.split(new_root, 0)
+            self.root = new_root
+
+        self._insert_non_full(self.root, key)
+
+    def _insert_non_full(self, node: BTreeNode, key: int) -> None:
+        """
+        Insert a key into a node that is not full.
+
+        Args:
+            node: The node to insert into
+            key: The key to insert
+        """
+        i = len(node.keys) - 1
+
+        if node.is_leaf:
+            node.keys.append(0)
+            while i >= 0 and key < node.keys[i]:
+                node.keys[i + 1] = node.keys[i]
+                i -= 1
+            node.keys[i + 1] = key
+        else:
+            while i >= 0 and key < node.keys[i]:
+                i -= 1
+            i += 1
+
+            if len(node.children[i].keys) >= self.max_keys:
+                node.children[i].split(node, i)
+                if key > node.keys[i]:
+                    i += 1
+
+            self._insert_non_full(node.children[i], key)
+
+    def traverse(self, node: BTreeNode | None = None) -> list[int]:
+        """
+        Traverse the B-Tree in sorted order.
+
+        Args:
+            node: The node to start traversal from (defaults to root)
+
+        Returns:
+            List of all keys in sorted order
+
+        >>> btree = BTree(order=3)
+        >>> for i in [10, 20, 5, 6, 12, 30, 7, 17]:
+        ...     btree.insert(i)
+        >>> btree.traverse()
+        [5, 6, 7, 10, 12, 17, 20, 30]
+        """
+        if node is None:
+            node = self.root
+
+        result: list[int] = []
+        i = 0
+
+        for i in range(len(node.keys)):
+            if not node.is_leaf:
+                result.extend(self.traverse(node.children[i]))
+            result.append(node.keys[i])
+
+        if not node.is_leaf:
+            result.extend(self.traverse(node.children[i + 1]))
+
+        return result
+
+    def get_height(self, node: BTreeNode | None = None) -> int:
+        """
+        Get the height of the B-Tree.
+
+        Args:
+            node: The node to start from (defaults to root)
+
+        Returns:
+            The height of the tree
+
+        >>> btree = BTree(order=3)
+        >>> btree.get_height()
+        0
+        >>> btree.insert(10)
+        >>> btree.get_height()
+        0
+        >>> for i in range(20):
+        ...     btree.insert(i)
+        >>> btree.get_height() > 0
+        True
+        """
+        if node is None:
+            node = self.root
+
+        if node.is_leaf:
+            return 0
+
+        return 1 + self.get_height(node.children[0])
+
+    def __str__(self) -> str:
+        """
+        String representation of the B-Tree.
+
+        Returns:
+            String showing all keys in sorted order
+        """
+        return f"BTree(order={self.order}, keys={self.traverse()})"
+
+
+if __name__ == "__main__":
+    import doctest
+
+    doctest.testmod()
+
+    btree = BTree(order=3)
+    keys = [10, 20, 5, 6, 12, 30, 7, 17, 3, 8, 15, 25, 35, 40]
+
+    print("Inserting keys:", keys)
+    for key in keys:
+        btree.insert(key)
+
+    print("\nB-Tree traversal (sorted):", btree.traverse())
+    print("B-Tree height:", btree.get_height())
+    print("\nSearching for 12:", btree.search(12))
+    print("Searching for 100:", btree.search(100))