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1181Publicado 2017Materias:Universidad Loyola - Universidad Loyola Granada (Otras Fuentes: Biblioteca de la Universidad Pontificia de Salamanca)Enlace del recurso
Libro electrónico -
1182Publicado 2021Materias:Biblioteca de la Universidad Pontificia de Salamanca (Otras Fuentes: Biblioteca Universitat Ramon Llull, Universidad Loyola - Universidad Loyola Granada)Acceso restringido con credenciales UPSA
Libro electrónico -
1183Publicado 2004Materias:Biblioteca Universitat Ramon Llull (Otras Fuentes: Biblioteca de la Universidad Pontificia de Salamanca)Libro
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1190Publicado 1925Materias: “…Mines Aspectes econòmics…”
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1193Publicado 2012Materias:Libro electrónico
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1195Publicado 2020Materias:Electrónico
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1196Publicado 2018Materias: “…Data mining…”
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1198Publicado 2019Tabla de Contenidos: “…Step 3: Execution and Interpretation -- Step 4: Using MetaCost -- Step 5: Applying the Model to an Unseen Dataset -- 5.2.3 Summary Points -- 5.3 Conclusion -- References -- 6 Association Analysis -- 6.1 Mining Association Rules -- 6.1.1 Itemsets -- Support -- Confidence -- Lift -- Conviction -- 6.1.2 Rule Generation -- 6.2 Apriori Algorithm -- 6.2.1 How it Works -- Frequent Itemset Generation -- Rule Generation -- 6.3 Frequent Pattern-Growth Algorithm -- 6.3.1 How it Works -- Frequent Itemset Generation -- 6.3.2 How to Implement -- Step 1: Data Preparation -- Step 2: Modeling Operator and Parameters -- Step 3: Create Association Rules -- Step 4: Interpreting the Results -- 6.4 Conclusion -- References -- 7 Clustering -- Clustering to Describe the Data -- Clustering for Preprocessing -- Types of Clustering Techniques -- 7.1 k-Means Clustering -- 7.1.1 How It Works -- Step 1: Initiate Centroids -- Step 2: Assign Data Points -- Step 3: Calculate New Centroids -- Step 4: Repeat Assignment and Calculate New Centroids -- Step 5: Termination -- Special Cases -- Evaluation of Clusters -- 7.1.2 How to Implement -- Step 1: Data Preparation -- Step 2: Clustering Operator and Parameters -- Step 3: Evaluation -- Step 4: Execution and Interpretation -- 7.2 DBSCAN Clustering -- 7.2.1 How It Works -- Step 1: Defining Epsilon and MinPoints -- Step 2: Classification of Data Points -- Step 3: Clustering -- Optimizing Parameters -- Special Cases: Varying Densities -- 7.2.2 How to Implement -- Step 1: Data Preparation -- Step 2: Clustering Operator and Parameters -- Step 3: Evaluation -- Step 4: Execution and Interpretation -- 7.3 Self-Organizing Maps -- 7.3.1 How It Works -- Step 1: Topology Specification -- Step 2: Initialize Centroids -- Step 3: Assignment of Data Objects -- Step 4: Centroid Update -- Step 5: Termination -- Step 6: Mapping a New Data Object…”
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1199Publicado 2018Materias: “…Data mining…”
Libro electrónico -
1200Publicado 2015Materias: “…Data mining…”
Libro electrónico
