You can use a hash table to track visited nodes, two pointers to detect cycles, or recursion to check for cycles, making all methods valid.

Arrays are used to store pixel data in image processing applications, where each element represents a pixel's color value.

Neural networks are used for object detection in autonomous vehicles, helping them identify pedestrians, other vehicles, and obstacles.

Trees are commonly used to represent hierarchical data, such as file systems, where each node can have multiple children.

Trees are used for hierarchical data representation, such as file systems and organizational structures.

By modifying the mid-point logic to continue searching in the left half even after finding the target.

Binary trees can be used in AI for decision trees, which help in making decisions based on various conditions.

Binary trees can represent decision trees in AI, where each node represents a decision point leading to different outcomes.

Clustering can be applied in anomaly detection by identifying outliers that do not fit well into any cluster.

Clustering can be applied in healthcare to group patients with similar symptoms, aiding in diagnosis and treatment planning.

Clustering can be used in healthcare to group patients with similar symptoms, aiding in diagnosis and treatment planning.

Decision Trees can segment customers by analyzing their purchasing behavior, helping target marketing efforts.

Linked lists can maintain a history of actions, allowing for easy traversal back to previous states for undo functionality.

Stacks can be used to check for balanced parentheses by pushing opening ones and popping when a closing one is encountered.

To improve a linear regression model that is underfitting, you can add more features to capture the underlying patterns in the data.

Transforming variables can help meet the assumptions of linear regression and improve model performance.

AVL trees ensure balance after insertion by performing multiple rotations as needed based on the balance factors of the nodes.

When an insertion causes an imbalance in an AVL tree, it is corrected by performing either a single or a double rotation, depending on the case.

AVL trees maintain balance by performing rotations (single or double) after insertions that cause imbalance.

Decision Trees create binary splits based on the categories of the categorical variables.

Decision Trees can use surrogate splits to handle missing values effectively.

Neural networks analyze customer data to tailor marketing strategies and recommendations to individual preferences.

Neural networks analyze user behavior and preferences to provide personalized product recommendations in e-commerce.

Random Forests improve accuracy by averaging the predictions from multiple Decision Trees.

Stacks keep track of local variables and return addresses during function calls, enabling proper execution flow.

Support Vector Machines can be sensitive to outliers, as they aim to maximize the margin based on the support vectors, which may include outliers.

The height of a binary tree is defined as the maximum depth of any node, which is the longest path from the root to a leaf.

The height of a binary tree is defined as the number of edges on the longest path from the root to a leaf node.

A left rotation involves moving the right child of a node up to take its place, while the current node becomes the left child of the new root.

A left rotation involves making the right child the new root of the subtree and adjusting the left child accordingly.