What is Precision and Recall? When evaluating a classification model's performance, it's crucial to understand its effectiveness at making predictions. Two essential metrics that help assess this...

What is Precision and Recall? When evaluating a classification model's performance, it's crucial to understand its effectiveness at making predictions. Two essential metrics that help assess this...
What is a Confusion Matrix? A confusion matrix is a fundamental tool used in machine learning and statistics to evaluate the performance of a classification model. At its core, a tablet lets you...
What is Ordinary Least Squares (OLS)? Ordinary Least Squares (OLS) is a fundamental technique in statistics and econometrics used to estimate the parameters of a linear regression model. In simple...
What is the METEOR Score? The METEOR score, which stands for Metric for Evaluation of Translation with Explicit ORdering, is a metric designed to evaluate the text quality generated by machine...
What is BERTScore? BERTScore is an innovative evaluation metric in natural language processing (NLP) that leverages the power of BERT (Bidirectional Encoder Representations from Transformers) to...
Introduction to Perplexity in NLP In the rapidly evolving field of Natural Language Processing (NLP), evaluating the effectiveness of language models is crucial. One of the key metrics used for this...
What is the BLEU Score in NLP? BLEU, Bilingual Evaluation Understudy, is a metric used to evaluate the quality of machine-generated text in NLP, most commonly in machine translation. Kishore...
What is the ROUGE Metric? ROUGE, which stands for Recall-Oriented Understudy for Gisting Evaluation, is a set of metrics used to evaluate the quality of summaries and translations generated by...
What is Normalised Discounted Cumulative Gain (NDCG)? Normalised Discounted Cumulative Gain (NDCG) is a popular evaluation metric used to measure the effectiveness of search engines, recommendation...
What is Mean Reciprocal Rank (MRR)? Mean Reciprocal Rank (MRR) is a metric used to evaluate the effectiveness of information retrieval systems, such as search engines and recommendation systems. It...
What is Ethical AI? Ethical AI involves developing and deploying artificial intelligence systems prioritising fairness, transparency, accountability, and respect for user privacy and autonomy. It...
What are Ranking Algorithms? Ranking algorithms are computational processes used to order items, such as web pages, products, or multimedia content, based on their relevance or importance to a given...
What is Hashing? Hashing is used in computer science as a data structure to store and retrieve data efficiently. At its core, hashing involves taking an input (or "key") and running it through a...
What are ROC and AUC Curves in Machine Learning? The ROC Curve The ROC (Receiver Operating Characteristic) curve is a graphical representation used to evaluate the performance of binary...
What is Naive Bayes? Naive Bayes classifiers are a group of supervised learning algorithms based on applying Bayes' Theorem with a strong (naive) assumption that every feature in the dataset is...
What is One-Class SVM? One-class SVM (Support Vector Machine) is a specialised form of the standard SVM tailored for unsupervised learning tasks, particularly anomaly detection. Unlike traditional...
What are Decision Trees? Decision trees are versatile and intuitive machine learning models for classification and regression tasks. It represents decisions and their possible consequences,...
What is an Isolation Forest? Isolation Forest, often abbreviated as iForest, is a powerful and efficient algorithm designed explicitly for anomaly detection. Introduced by Fei Tony Liu, Kai Ming...
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