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- Multi-layer Perceptron Classifier Description: The multilayer perceptron (MLP) classifier is a supervised learning model based on a neural network architecture. This structure(...) Read more
- Multi-instance Learning Description: Multi-instance learning is a variant of supervised learning where a single label is associated with a set of instances, but the(...) Read more
- Misclassification Description: Misclassification refers to the incorrect assignment of a label to a data point in classification tasks within supervised learning.(...) Read more
- Model-Based Clustering Description: Model-Based Clustering is a clustering approach that assumes that the data is generated from a mixture of underlying probability(...) Read more
- Markov Clustering Description: Markov Clustering is a graph clustering algorithm that uses random walks to find clusters in graphs by simulating random walks and(...) Read more
- Mixture Models Description: A mixture model is a probabilistic model that assumes that data is generated from a mixture of several distributions. These models(...) Read more
- Minimum Spanning Tree Description: A Minimum Spanning Tree is a subset of the edges of a connected, weighted graph that connects all vertices without cycles and with(...) Read more
- MDS (Multidimensional Scaling) Description: Multidimensional Scaling (MDS) is a statistical technique used to visualize the similarity or dissimilarity between data points by(...) Read more
- Multi-Cluster Analysis Description: Multi-Cluster Analysis involves identifying multiple clusters within a dataset, allowing for more nuanced insights into the data.(...) Read more
- Multivariate Gaussian Mixture Description: A Multivariate Gaussian Mixture is a probabilistic model that represents the presence of subpopulations within a general(...) Read more
- Multi-dimensional Clustering Description: Multi-dimensional clustering refers to clustering techniques that operate on data with multiple dimensions, allowing for the(...) Read more
- Multi-label Clustering Description: Multi-label clustering is a clustering approach that allows each data point to belong to multiple clusters simultaneously. Unlike(...) Read more
- Meta Clustering Description: Meta Clustering is a technique that involves grouping the results of multiple clustering algorithms to improve overall clustering(...) Read more
- Multiscale Clustering Description: Multiscale Clustering is a method that identifies clusters at different scales, allowing for a more comprehensive understanding of(...) Read more
- Multi-criteria Decision Making Description: Multicriteria Decision Making (MCDM) is an analytical approach that allows decision-makers to evaluate and select among multiple(...) Read more
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