Machine Learning Activities Machine Learning (ML) is a branch of Artificial Intelligence that enables computers to learn from data and make predictions or decisions without being explicitly programmed. ML models go through several key activities to ensure they function effectively. These activities include data collection, data preprocessing, model selection, model training, and evaluation. Data Collection Data […]
Unsupervised Learning Unsupervised Learning is a type of Machine Learning where a model learns patterns from data without any labeled examples without any guidance. Unlike supervised learning, where the model is trained using input-output pairs, unsupervised learning finds hidden structures and relationships in the data on its own. How Unsupervised Learning works? In Unsupervised learning, […]
IAssert and IAssertLifecycle in TestNG In TestNG, IAssert and IAssertLifecycle are interfaces used internally for handling assertions, especially with SoftAssert. IAssert IAssert is an interface that represents a single assertion operation. It contains the details required to perform an assertion such as the expected value, actual value, and assertion message. Main Purpose: Represents an individual […]
Supervised Learning Supervised Learning is a type of Machine Learning where a model learns from labeled data.In this method the model is trained with labeled datasets. This means that the model is provided with input-output pairs, where the input data has corresponding correct outputs. How Supervised Learning Works? Supervised Learning involves training a model using a […]
Model Performance using F1 Score In machine learning, evaluating a model’s performance is crucial. One common metric used for classification problems is the F1 Score. It helps measure how well a model balances precision and recall. This is especially useful when dealing with imbalanced datasets where accuracy alone can be misleading. Precision and Recall Before […]
Fuzzy C-Means Clustering Algorithm Clustering is a fundamental technique in machine learning and data analysis used to group similar data points together. One of the widely used clustering algorithms is the Fuzzy C-Means (FCM) algorithm, which is an extension of K-Means clustering but allows data points to belong to multiple clusters with different degrees of […]
