LogLikelihood equal to 1 to ignore data contribution and focus on prior.
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#include <Null_likelihood.hpp>
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| | Null_likelihood (const Data &data) |
| double | cluster_loglikelihood (int cluster_index) const override final |
| | Computes the full log-likelihood for a cluster.
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| double | cluster_loglikelihood (int cluster_index, const Eigen::Ref< const Eigen::VectorXi > &cls_ass_k) const override final __attribute__((hot)) |
| | Computes the full log-likelihood for a cluster with given assignments.
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| double | point_loglikelihood_cond (int point_index, int cluster_index) const override final __attribute__((hot)) |
| | Computes the conditional log-likelihood of a point given a cluster.
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| | Likelihood (const Data &data) |
| virtual double | clusters_loglikelihood (int c1, int c2) const |
| | Computes the joint log-likelihood for two clusters.
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| virtual | ~Likelihood ()=default |
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| const Data & | data |
| | Reference to Data object with distances and allocations.
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LogLikelihood equal to 1 to ignore data contribution and focus on prior.
◆ Null_likelihood()
| Null_likelihood::Null_likelihood |
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const Data & | data | ) |
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inline |
◆ cluster_loglikelihood() [1/2]
| double Null_likelihood::cluster_loglikelihood |
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int | cluster_index | ) |
const |
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inlinefinaloverridevirtual |
Computes the full log-likelihood for a cluster.
- Parameters
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| cluster_index | Index of the cluster to evaluate |
- Returns
- Total log-likelihood (cohesion + repulsion)
This method computes both the within-cluster cohesion and the between-cluster repulsion contributions for the specified cluster.
Implements Likelihood.
◆ cluster_loglikelihood() [2/2]
| double Null_likelihood::cluster_loglikelihood |
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int | cluster_index, |
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const Eigen::Ref< const Eigen::VectorXi > & | cls_ass_k ) const |
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inlinefinaloverridevirtual |
Computes the full log-likelihood for a cluster with given assignments.
- Parameters
-
| cluster_index | Index of the cluster to evaluate |
| cls_ass_k | Vector of point indices in the cluster |
- Returns
- Total log-likelihood (cohesion + repulsion)
This overload allows computing the likelihood with a custom set of cluster assignments without modifying the data structure.
Implements Likelihood.
◆ point_loglikelihood_cond()
| double Null_likelihood::point_loglikelihood_cond |
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int | point_index, |
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int | cluster_index ) const |
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inlinefinaloverridevirtual |
Computes the conditional log-likelihood of a point given a cluster.
- Parameters
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| point_index | Index of the point to evaluate |
| cluster_index | Index of the target cluster |
- Returns
- Conditional log-likelihood of assigning the point to the cluster
This method evaluates how well a point fits into a specific cluster, considering both its cohesion with points in that cluster and its repulsion from points in other clusters.
Implements Likelihood.
The documentation for this class was generated from the following file: