A dendrogram visually represents the arrangement of clusters in hierarchical clustering.

A dendrogram is a tree-like diagram that illustrates the arrangement of clusters formed during hierarchical clustering.

Linkage in hierarchical clustering refers to the strategy used to determine the distance between clusters, which affects how clusters are merged.

Agglomerative clustering is a bottom-up approach where each data point starts as its own cluster and pairs of clusters are merged as one moves up the hierarchy.

Agglomerative clustering starts with individual points and merges them into clusters, while divisive clustering starts with one cluster and splits it into smaller clusters.

A dendrogram visually represents the arrangement of clusters and the distances at which they are merged.

The agglomerative approach in hierarchical clustering starts with individual data points and merges them into larger clusters based on similarity.

In HTTP/1.1, connections are persistent by default, meaning that multiple requests can be sent over a single connection without reopening it.

A subnet mask of 255.255.255.0 indicates a Class C network, allowing for 256 IP addresses in total.

The subnet mask determines the network portion of an IP address, allowing devices to identify which part of the address refers to the network and which part refers to the host.

The broadcast address is used to send data to all devices within a specific subnet.

Supernetting refers to the practice of combining multiple smaller subnets into a larger network to simplify routing.

In IPv6, the prefix length indicates the number of bits used for the network portion, similar to a subnet mask in IPv4.

'K' represents the number of clusters that the algorithm will create from the data.

If K is set too high, the model may overfit the data, resulting in too many clusters that do not generalize well.

Poorly chosen initial centroids can lead K-means to converge to a local minimum rather than the global minimum, resulting in suboptimal clustering.

A token is a data structure that represents a keyword, identifier, or other meaningful element in the source code.

Multicollinearity refers to a situation where independent variables in a regression model are highly correlated with each other.

Overfitting occurs when a model learns the noise in the training data instead of the actual underlying pattern, leading to poor performance on unseen data.

A residual is the difference between the observed value and the predicted value in a regression model.

The slope indicates how much the dependent variable is expected to increase (or decrease) when the independent variable increases by one unit.

Logistic regression outputs a probability between 0 and 1, which can be thresholded to classify data points into binary categories.

The 'shift' action in LR parsing moves the input pointer to the next token.

The primary operation in Merge Sort to combine two sorted arrays is called merging.

Merging two sorted arrays takes O(n) time, where n is the total number of elements in both arrays.

Neural networks are used in natural language processing for tasks such as language translation, enabling machines to understand and convert text from one language to another.

Neural networks are effective in sentiment analysis, where they can determine the emotional tone behind a body of text.

In Python, a list can be used as a stack by using append() to push and pop() to remove the top element.

In Python, a list can be used as a stack by using append() to push and pop() to remove elements.

A list in Python can be used to implement a queue, although collections.deque is more efficient for this purpose.