Methodology u DM Data Mining u Methodology Methodology
- Slides: 59
DM Methodology (注) u DM: Data Mining (データマイニング) u Methodology: 方法論
DM Methodology 1. Exploratory data analysis (探索的データ解析) 2. Computational data mining (計算論的データマイニング) 3. Statistical data mining (統計的データマイニング)
DM Methodology 1. Exploratory data analysis (探索的データ解析) 2. Computational data mining (計算論的データマイニング) 3. Statistical data mining (統計的データマイニング)
1.Exploratory data analysis a. 統計的データ解析(SDA) b. 探索的データ解析(EDA)
探索的データ解析(EDA) 1. 2. 3. 4. 5. 6. 7. 幹葉表示(stem-and-leaf display) 要約値(letter value display) 箱ヒゲ図(box-whisker plots) X-Y表示(X-Y plotting) 抵抗性のある直線回帰(registant line) 中央値分散分析(median polish) 時系列データのならし(smoothing)
DM Methodology 1. Exploratory data analysis (探索的データ解析) 2. Computational data mining (計算論的データマイニング) 3. Statistical data mining (統計的データマイニング)
3.Statistical data mining a. b. c. d. e. f. Statistic models(統計モデル) Statistic inference(統計的推論) Non-parametric model General linear model Log-linear model Graphical model etc.
DM Methodology 1. Exploratory data analysis (探索的データ解析) 2. Computational data mining (計算論的データマイニング) 3. Statistical data mining (統計的データマイニング)
2.Computational data mining 1. 2. 3. 4. 5. 6. Cluster analysis(クラスター分析) Tree models(木モデル) Linear regression(線形回帰) Logistic regression(ロジスティック回帰) Neural networks(ニューラルネットワーク) ILP(Inductive Logic Programming; 帰納論理プログラミング) 7. SVM(support vector machines) etc.
2.Computational data mining a. b. c. d. e. f. Tree models(木モデル) Cluster analysis(クラスター分析) Linear regression(線形回帰) Logistic regression(ロジスティック回帰) Neural networks(ニューラルネットワーク) ILP(Inductive Logic Programming; 帰納論理プログラミング) etc.
a.クラスター分析 i. Hierarchical methods(階層型法) ii. Non-hierarchical methods(非階層型法)
- Mining complex types of data in data mining
- Mining multimedia databases in data mining
- Strip mining vs open pit mining
- Strip mining before and after
- Difference between strip mining and open pit mining
- Web text mining
- Data reduction in data mining
- What is kdd process in data mining
- What is missing data in data mining
- Concept hierarchy generation for nominal data
- Data reduction in data mining
- Data reduction in data mining
- Data cube technology in data mining
- Data reduction in data mining
- Arsitektur data mining
- Perbedaan data warehouse dan data mining
- Crm data warehouse models
- Complex data types in data mining
- Data warehousing data mining and olap
- Noisy data in data mining
- Three-tier data warehouse architecture
- Markku roiha
- Data compression in data mining
- Introduction to data warehousing and data mining
- Data warehouse dan data mining
- Cs 412 introduction to data mining
- Data mining major issues
- Unsupervised learning in data mining
- Motivation for data mining
- Data mining slides
- Query tools in data mining
- Pump it up: data mining the water table
- Tahapan utama pada proses data mining
- Peran utama data mining adalah sebagai berikut
- Olap stands for *
- Bloom filter for stream data mining
- Data mining steps
- Data mining midterm exam with solutions
- Multidimensional space in data mining
- Data mining roadmap
- Weka pentaho
- Spatial data mining applications
- Walmart data mining
- Ibm data mining
- Spss data mining
- Frequent itemset mining methods
- Objective of data mining
- Emr data mining
- Cur decomposition in data mining
- Dss in data mining
- Data maining
- Overfitting in data mining
- Svd data mining
- Data mining lectures
- Data mining functionality
- Nominal attribute in data mining
- Correlation data mining
- Types of attributes in data mining
- Confluence of multiple disciplines in data mining
- Information gain in data mining