Text Classification
Unlock automated text categorization in your workflows with the Text Classification component for FlowHunt. Effortlessly classify input text into user-defined c...
3 min read
AI
Classification
+3
Classification
Area Under the Curve (AUC)
The Area Under the Curve (AUC) is a fundamental metric in machine learning used to evaluate the performance of binary classification models. It quantifies the o...
3 min read
Machine Learning
AI
+3
Classifier
An AI classifier is a machine learning algorithm that assigns class labels to input data, categorizing information into predefined classes based on learned patt...
10 min read
AI
Classifier
+3
Confusion Matrix
A confusion matrix is a machine learning tool for evaluating the performance of classification models, detailing true/false positives and negatives to provide i...
6 min read
Machine Learning
Classification
+3
Cross-Entropy
Cross-entropy is a pivotal concept in both information theory and machine learning, serving as a metric to measure the divergence between two probability distri...
4 min read
Cross-Entropy
Machine Learning
+3
Decision Tree
A decision tree is a powerful and intuitive tool for decision-making and predictive analysis, used in both classification and regression tasks. Its tree-like st...
6 min read
Decision Trees
Machine Learning
+5
Discriminative Models
Learn about Discriminative AI Models—machine learning models focused on classification and regression by modeling decision boundaries between classes. Understan...
7 min read
Discriminative Models
AI
+6
Gradient Boosting
Gradient Boosting is a powerful machine learning ensemble technique for regression and classification. It builds models sequentially, typically with decision tr...
5 min read
Gradient Boosting
Machine Learning
+4
K-Nearest Neighbors
The k-nearest neighbors (KNN) algorithm is a non-parametric, supervised learning algorithm used for classification and regression tasks in machine learning. It ...
6 min read
Machine Learning
KNN
+3
LightGBM
LightGBM, or Light Gradient Boosting Machine, is an advanced gradient boosting framework developed by Microsoft. Designed for high-performance machine learning ...
5 min read
LightGBM
Machine Learning
+5
Log Loss
Log loss, or logarithmic/cross-entropy loss, is a key metric to evaluate machine learning model performance—especially for binary classification—by measuring th...
5 min read
Log Loss
Machine Learning
+3
Naive Bayes
Naive Bayes is a family of classification algorithms based on Bayes’ Theorem, applying conditional probability with the simplifying assumption that features are...
5 min read
Naive Bayes
Classification
+3
Recall in Machine Learning
Explore recall in machine learning: a crucial metric for evaluating model performance, especially in classification tasks where correctly identifying positive i...
9 min read
Machine Learning
Recall
+3
Supervised Learning
Supervised learning is a fundamental approach in machine learning and artificial intelligence where algorithms learn from labeled datasets to make predictions o...
10 min read
Supervised Learning
Machine Learning
+4
Supervised Learning
Supervised learning is a fundamental AI and machine learning concept where algorithms are trained on labeled data to make accurate predictions or classification...
3 min read
AI
Machine Learning
+3
Top-k Accuracy
Top-k accuracy is a machine learning evaluation metric that assesses if the true class is among the top k predicted classes, offering a comprehensive and forgiv...
5 min read
AI
Machine Learning
+3