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文档列表

04 Obtaining Prediction Models/002 Creating Prediction Models.mp4 112.0 MB
04 Obtaining Prediction Models/003 Examine Alternative Regression Models.mp4 110.1 MB
04 Obtaining Prediction Models/004 Regression Trees.mp4 100.6 MB
07 Pre-Processing the Data to Apply Methodology/004 Pre-Processing the Data part 3.mp4 96.2 MB
01 A Brief Introduction to R and RStudio using Scripts/002 Introduction to R for Data Mining.mp4 92.2 MB
07 Pre-Processing the Data to Apply Methodology/008 Lift Charts and Precision Recall Curves.mp4 91.3 MB
03 Introduction to Predicting Algae Blooms/009 Imputation Replace Missing Values through Correlation.mp4 89.9 MB
10 Sidebar on Boosting/005 Boosting Extensions and Variants.mp4 89.0 MB
01 A Brief Introduction to R and RStudio using Scripts/007 Generating Sequences.mp4 88.6 MB
10 Sidebar on Boosting/004 Replicating Adaboost using Rpart part 2.mp4 87.6 MB
07 Pre-Processing the Data to Apply Methodology/005 Defining Data Mining Tasks.mp4 85.6 MB
03 Introduction to Predicting Algae Blooms/006 Imputation Dealing with Unknown or Missing Values.mp4 84.0 MB
07 Pre-Processing the Data to Apply Methodology/001 Review the Data and the Focus of the Fraudulent Transactions Case.mp4 82.9 MB
14 Model Evaluation and Selection/008 Set Up Ranksystems.mp4 82.1 MB
04 Obtaining Prediction Models/001 Read in Data Files.mp4 81.8 MB
05 Evaluating and Selecting Models/001 Alternative Model Evaluation Criteria.mp4 79.8 MB
12 Prediction Tasks and Models/008 Create Initial Model part 2.mp4 79.2 MB
11 Introduction to Stock Market Prediction Case Study/007 Defining the Prediction Tasks part 2.mp4 79.0 MB
05 Evaluating and Selecting Models/008 Predicting from the Models.mp4 78.7 MB
09 The Data Mining Tasks to Find the Fraudulent Transactions/007 Supervised and Unsupervised Approaches.mp4 77.7 MB
10 Sidebar on Boosting/003 Replicating Adaboost using Rpart Recursive Partitioning Package.mp4 76.6 MB
05 Evaluating and Selecting Models/003 Setting up K-Fold Evaluation part 1.mp4 75.7 MB
12 Prediction Tasks and Models/011 Neural Network Prediction Technique part 1.mp4 75.6 MB
14 Model Evaluation and Selection/002 Begin Evaluating Models.mp4 75.3 MB
03 Introduction to Predicting Algae Blooms/001 Predicting Algae Blooms.mp4 74.4 MB
08 Methodology to Find Outliers Fraudulent Transactions/007 Experimental Methodology to find Outliers part 2.mp4 74.1 MB
11 Introduction to Stock Market Prediction Case Study/002 Case Study Background and Data part 1.mp4 73.3 MB
01 A Brief Introduction to R and RStudio using Scripts/014 Creating New Functions.mp4 73.1 MB
15 Wrap Up Stock Market Case Study/001 Prologue to Last Session Wrap-Up.mp4 72.8 MB
11 Introduction to Stock Market Prediction Case Study/003 Case Study Background and Data part 2.mp4 71.7 MB
09 The Data Mining Tasks to Find the Fraudulent Transactions/005 Local Outlier Factors.mp4 70.9 MB
08 Methodology to Find Outliers Fraudulent Transactions/008 Experimental Methodology to find Outliers part 3.mp4 70.8 MB
05 Evaluating and Selecting Models/009 Comparing the Predictions.mp4 70.2 MB
05 Evaluating and Selecting Models/002 Introduction to K-Fold Cross-Validation.mp4 69.2 MB
05 Evaluating and Selecting Models/007 Finish Evaluating Models.mp4 68.9 MB
03 Introduction to Predicting Algae Blooms/008 Imputation Replace Missing Values with Central Measures.mp4 68.8 MB
04 Obtaining Prediction Models/005 Strategy for Pruning Trees.mp4 68.0 MB
12 Prediction Tasks and Models/012 Neural Network Prediction Technique part 2.mp4 68.0 MB
12 Prediction Tasks and Models/004 Decision Trees part 3.mp4 67.6 MB
12 Prediction Tasks and Models/007 Create Initial Model part 1.mp4 67.1 MB
08 Methodology to Find Outliers Fraudulent Transactions/009 Experimental Methodology to find Outliers part 4.mp4 67.0 MB
06 Examine the Data in the Fraudulent Transactions Case Study/004 Exploring the Data with Eye toward Missingness.mp4 66.9 MB
03 Introduction to Predicting Algae Blooms/002 Visualizing other Imputations with Lattice Plots.mp4 66.9 MB
03 Introduction to Predicting Algae Blooms/003 Data Visualization and Summarization Histograms.mp4 66.5 MB
11 Introduction to Stock Market Prediction Case Study/006 Defining the Prediction Tasks part 1.mp4 66.2 MB
07 Pre-Processing the Data to Apply Methodology/002 Pre-Processing the Data part 1.mp4 66.1 MB
14 Model Evaluation and Selection/007 Experimental Model Comparisons part 2.mp4 65.8 MB
14 Model Evaluation and Selection/010 Continue Evaluating part 2.mp4 65.8 MB
01 A Brief Introduction to R and RStudio using Scripts/011 Data Structures Lists.mp4 64.8 MB
09 The Data Mining Tasks to Find the Fraudulent Transactions/008 SMOTE and Naive Bayes part 1.mp4 64.4 MB
12 Prediction Tasks and Models/003 Decision Trees part 2.mp4 63.6 MB
03 Introduction to Predicting Algae Blooms/005 Data Visualization Conditioning Plots.mp4 63.5 MB
15 Wrap Up Stock Market Case Study/002 Last Session Wrap-Up part 1.mp4 63.2 MB
11 Introduction to Stock Market Prediction Case Study/008 Defining the Prediction Tasks part 3.mp4 62.7 MB
02 Inputting and Outputting Data and Text/008 Reading and Writing Files part 2.mp4 62.1 MB
09 The Data Mining Tasks to Find the Fraudulent Transactions/001 Review of Fraud Case part 1.mp4 61.6 MB
02 Inputting and Outputting Data and Text/004 Using readLines Function and Text Data.mp4 61.3 MB
08 Methodology to Find Outliers Fraudulent Transactions/006 Experimental Methodology to find Outliers part 1.mp4 60.3 MB
03 Introduction to Predicting Algae Blooms/007 Imputation Removing Rows with Missing Values.mp4 60.2 MB
14 Model Evaluation and Selection/006 Experimental Model Comparisons part 1.mp4 59.9 MB
01 A Brief Introduction to R and RStudio using Scripts/013 Data Structures Dataframes part 2.mp4 59.8 MB
09 The Data Mining Tasks to Find the Fraudulent Transactions/002 Review of Fraud Case part 2.mp4 59.5 MB
07 Pre-Processing the Data to Apply Methodology/003 Pre-Processing the Data part 2.mp4 59.0 MB
14 Model Evaluation and Selection/001 Quick Review of Case Study Support Vector Machines SVMs.mp4 58.7 MB
14 Model Evaluation and Selection/009 Continue Evaluating part 1.mp4 58.5 MB
05 Evaluating and Selecting Models/006 Best Model part 2.mp4 58.3 MB
09 The Data Mining Tasks to Find the Fraudulent Transactions/003 Review of Fraud Case part 3.mp4 57.9 MB
05 Evaluating and Selecting Models/004 Setting up K-Fold Evaluation part 2.mp4 57.5 MB
07 Pre-Processing the Data to Apply Methodology/007 Precision and Recall.mp4 57.2 MB
14 Model Evaluation and Selection/011 Continue Evaluating part 3.mp4 57.0 MB
10 Sidebar on Boosting/001 Introduction to Boosting from Rattle course.mp4 56.9 MB
11 Introduction to Stock Market Prediction Case Study/004 Accessing the Data part 1.mp4 55.9 MB
08 Methodology to Find Outliers Fraudulent Transactions/004 Cumulative Recall Chart.mp4 54.9 MB
01 A Brief Introduction to R and RStudio using Scripts/006 Factors part 2.mp4 54.4 MB
10 Sidebar on Boosting/002 Boosting Demo Basics using R.mp4 54.4 MB
09 The Data Mining Tasks to Find the Fraudulent Transactions/009 SMOTE and Naive Bayes part 2.mp4 54.1 MB
13 Prediction Models and Support Vector Machines SVMs/004 SVMs Applied to Stock Market Case.mp4 54.0 MB
13 Prediction Models and Support Vector Machines SVMs/006 Multivariate Adaptive Regressive Splines.mp4 53.3 MB
13 Prediction Models and Support Vector Machines SVMs/009 Writing a Simulated Trader Function part 1.mp4 53.0 MB
15 Wrap Up Stock Market Case Study/003 Last Session Wrap-Up part 2.mp4 52.5 MB
09 The Data Mining Tasks to Find the Fraudulent Transactions/006 Plotting Everything.mp4 52.2 MB
13 Prediction Models and Support Vector Machines SVMs/007 How Will the Predictions be Used .mp4 52.1 MB
01 A Brief Introduction to R and RStudio using Scripts/012 Data Structures Dataframes part 1.mp4 51.7 MB
08 Methodology to Find Outliers Fraudulent Transactions/003 Review Lift Charts and Precision Recall Curves.mp4 51.7 MB
06 Examine the Data in the Fraudulent Transactions Case Study/005 Continue Exploring the Data.mp4 51.7 MB
14 Model Evaluation and Selection/003 Evaluating Policy One and Policy Two.mp4 51.3 MB
02 Inputting and Outputting Data and Text/005 Example Program powers.R.mp4 50.7 MB
02 Inputting and Outputting Data and Text/006 Example Program quad2b.R.mp4 50.7 MB
08 Methodology to Find Outliers Fraudulent Transactions/002 Review Precision and Recall.mp4 50.5 MB
03 Introduction to Predicting Algae Blooms/004 Data Visualization Boxplot and Identity Plot.mp4 50.4 MB
12 Prediction Tasks and Models/010 Precision and Recall and Confusion Matrices.mp4 50.2 MB
07 Pre-Processing the Data to Apply Methodology/006 Semi-Supervised Techniques.mp4 50.1 MB
01 A Brief Introduction to R and RStudio using Scripts/004 Data Structures Vectors part 2.mp4 50.1 MB
13 Prediction Models and Support Vector Machines SVMs/002 Review Support Vector Machines SVMs using Weather Data part 2.mp4 49.9 MB
14 Model Evaluation and Selection/005 So What Approach is Recommended .mp4 49.8 MB
13 Prediction Models and Support Vector Machines SVMs/008 Two Strategies.mp4 49.7 MB
12 Prediction Tasks and Models/002 Decision Trees as Applicable to Case Study Tasks.mp4 49.1 MB
12 Prediction Tasks and Models/005 Decision Trees part 4.mp4 48.8 MB
12 Prediction Tasks and Models/009 The Prediction Tasks.mp4 48.2 MB
13 Prediction Models and Support Vector Machines SVMs/011 Evaluating our Simulated Trades.mp4 47.8 MB
12 Prediction Tasks and Models/006 Random Forests Review.mp4 47.2 MB
10 Sidebar on Boosting/006 Boosting Exercise.mp4 47.0 MB
14 Model Evaluation and Selection/004 Why You Cannot Randomly Resample Records.mp4 46.9 MB
05 Evaluating and Selecting Models/005 Best Model part 1.mp4 46.6 MB
02 Inputting and Outputting Data and Text/003 Using readline, cat and print Functions.mp4 46.1 MB
01 A Brief Introduction to R and RStudio using Scripts/003 Data Structures Vectors part 1.mp4 45.9 MB
11 Introduction to Stock Market Prediction Case Study/009 Defining the Prediction Tasks part 4.mp4 45.9 MB
13 Prediction Models and Support Vector Machines SVMs/001 Review Support Vector Machines SVMs using Weather Data part 1.mp4 45.4 MB
11 Introduction to Stock Market Prediction Case Study/005 Accessing the Data part 2.mp4 45.3 MB
01 A Brief Introduction to R and RStudio using Scripts/009 Data Structures Matrices and Arrays part 1.mp4 44.9 MB
11 Introduction to Stock Market Prediction Case Study/010 Defining the Prediction Tasks part 5.mp4 44.8 MB
01 A Brief Introduction to R and RStudio using Scripts/008 Indexing aka Subscripting or Subsetting.mp4 43.2 MB
01 A Brief Introduction to R and RStudio using Scripts/005 Factors part 1.mp4 42.9 MB
13 Prediction Models and Support Vector Machines SVMs/010 Writing a Simulated Trader Function part 2.mp4 42.7 MB
13 Prediction Models and Support Vector Machines SVMs/005 Kernel Functions.mp4 42.5 MB
01 A Brief Introduction to R and RStudio using Scripts/010 Data Structures Matrices and Arrays part 2.mp4 41.4 MB
09 The Data Mining Tasks to Find the Fraudulent Transactions/004 Baseline Boxplot Rule.mp4 40.4 MB
08 Methodology to Find Outliers Fraudulent Transactions/005 Creating More Functions for the Experimental Methodology.mp4 39.8 MB
13 Prediction Models and Support Vector Machines SVMs/003 Review Support Vector Machines SVMs using Weather Data part 3.mp4 38.0 MB
08 Methodology to Find Outliers Fraudulent Transactions/010 Experimental Methodology to find Outliers part 5.mp4 35.0 MB
02 Inputting and Outputting Data and Text/001 Using the scan Function for Input part 1.mp4 26.3 MB
02 Inputting and Outputting Data and Text/002 Using the scan Function for Input part 2.mp4 25.1 MB
02 Inputting and Outputting Data and Text/007 Reading and Writing Files part 1.mp4 23.7 MB
06 Examine the Data in the Fraudulent Transactions Case Study/001 Exercise Solution from Evaluating and Selecting Models.mp4 20.5 MB
06 Examine the Data in the Fraudulent Transactions Case Study/003 Prelude to Exploring the Data.mp4 20.4 MB
12 Prediction Tasks and Models/001 Prelude to Modeling Stock Market Indices.mp4 19.6 MB
11 Introduction to Stock Market Prediction Case Study/001 Introduction to Stock Market Case Study and Materials.mp4 15.7 MB
08 Methodology to Find Outliers Fraudulent Transactions/001 Exercise from Previous Session.mp4 13.4 MB
06 Examine the Data in the Fraudulent Transactions Case Study/002 Fraudulent Case Study Introduction.mp4 11.7 MB
01 A Brief Introduction to R and RStudio using Scripts/001 Course Overview.mp4 8.2 MB

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