Pages that link to "Item:Q1603342"
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The following pages link to Integration of self-organizing feature map and K-means algorithm for market segmentation (Q1603342):
Displaying 13 items.
- Application of ant \(K\)-means on clustering analysis (Q814126) (← links)
- Comparative performance of the FSCL neural net and \(K\)-means algorithm for market segmentation (Q1268170) (← links)
- Comparing performance of feedforward neural nets and \(K\)-means for cluster-based market segmentation (Q1296363) (← links)
- Extracting clusters from aggregate panel data: a market segmentation study (Q1734765) (← links)
- Application of connectionistic models for the evaluation of market structures (Q1976723) (← links)
- A trend based investment decision approach using clustering and heuristic algorithm (Q2335930) (← links)
- Dynamic segmentation with growth mixture models (Q2418269) (← links)
- A clustering method to identify representative financial ratios (Q2476753) (← links)
- A case study of using the generalized K-harmonic means method in decision-making processes (Q3633874) (← links)
- A bio-mimetic approach to marketing segmentation: Principles and comparative analysis (Q4504948) (← links)
- An extended study of the K-means algorithm for data clustering and its applications (Q4661248) (← links)
- Comparing Two-Stage Segmentation Methods for Choice Data with a One-Stage Latent Class Choice Analysis (Q4921623) (← links)
- Support Vector Clustering for Customer Segmentation on Mobile TV Service (Q5265804) (← links)
