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种子名称： Udemy - Case Studies in Data Mining with R
文件类型： 视频
文件数目： 130个文件
文件大小： 7.14 GB
收录时间： 2017-2-8 19:41
已经下载： 3次
资源热度： 210
最近下载： 2024-12-27 14:19

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Udemy - Case Studies in Data Mining with R.torrent

12 Prediction Tasks and Models/009 The Prediction Tasks.mp445.93MB

12 Prediction Tasks and Models/001 Prelude to Modeling Stock Market Indices.mp418.73MB

12 Prediction Tasks and Models/006 Random Forests Review.mp444.97MB

12 Prediction Tasks and Models/007 Create Initial Model part 1.mp464.02MB

12 Prediction Tasks and Models/005 Decision Trees part 4.mp446.5MB

12 Prediction Tasks and Models/002 Decision Trees as Applicable to Case Study Tasks.mp446.82MB

12 Prediction Tasks and Models/010 Precision and Recall and Confusion Matrices.mp447.85MB

12 Prediction Tasks and Models/011 Neural Network Prediction Technique part 1.mp472.14MB

12 Prediction Tasks and Models/003 Decision Trees part 2.mp460.62MB

12 Prediction Tasks and Models/004 Decision Trees part 3.mp464.46MB

12 Prediction Tasks and Models/008 Create Initial Model part 2.mp475.5MB

12 Prediction Tasks and Models/012 Neural Network Prediction Technique part 2.mp464.81MB

13 Prediction Models and Support Vector Machines SVMs/004 SVMs Applied to Stock Market Case.mp451.47MB

13 Prediction Models and Support Vector Machines SVMs/006 Multivariate Adaptive Regressive Splines.mp450.8MB

13 Prediction Models and Support Vector Machines SVMs/008 Two Strategies.mp447.44MB

13 Prediction Models and Support Vector Machines SVMs/003 Review Support Vector Machines SVMs using Weather Data part 3.mp436.2MB

13 Prediction Models and Support Vector Machines SVMs/007 How Will the Predictions be Used .mp449.7MB

13 Prediction Models and Support Vector Machines SVMs/002 Review Support Vector Machines SVMs using Weather Data part 2.mp447.56MB

13 Prediction Models and Support Vector Machines SVMs/009 Writing a Simulated Trader Function part 1.mp450.53MB

13 Prediction Models and Support Vector Machines SVMs/005 Kernel Functions.mp440.55MB

13 Prediction Models and Support Vector Machines SVMs/001 Review Support Vector Machines SVMs using Weather Data part 1.mp443.34MB

13 Prediction Models and Support Vector Machines SVMs/011 Evaluating our Simulated Trades.mp445.56MB

13 Prediction Models and Support Vector Machines SVMs/010 Writing a Simulated Trader Function part 2.mp440.69MB

03 Introduction to Predicting Algae Blooms/001 Predicting Algae Blooms.mp470.92MB

03 Introduction to Predicting Algae Blooms/009 Imputation Replace Missing Values through Correlation.mp485.69MB

03 Introduction to Predicting Algae Blooms/006 Imputation Dealing with Unknown or Missing Values.mp480.13MB

03 Introduction to Predicting Algae Blooms/007 Imputation Removing Rows with Missing Values.mp457.39MB

03 Introduction to Predicting Algae Blooms/008 Imputation Replace Missing Values with Central Measures.mp465.57MB

03 Introduction to Predicting Algae Blooms/005 Data Visualization Conditioning Plots.mp460.59MB

03 Introduction to Predicting Algae Blooms/003 Data Visualization and Summarization Histograms.mp463.39MB

03 Introduction to Predicting Algae Blooms/002 Visualizing other Imputations with Lattice Plots.mp463.75MB

03 Introduction to Predicting Algae Blooms/004 Data Visualization Boxplot and Identity Plot.mp448.07MB

07 Pre-Processing the Data to Apply Methodology/006 Semi-Supervised Techniques.mp447.79MB

07 Pre-Processing the Data to Apply Methodology/005 Defining Data Mining Tasks.mp481.59MB

07 Pre-Processing the Data to Apply Methodology/008 Lift Charts and Precision Recall Curves.mp487.05MB

07 Pre-Processing the Data to Apply Methodology/004 Pre-Processing the Data part 3.mp491.74MB

07 Pre-Processing the Data to Apply Methodology/003 Pre-Processing the Data part 2.mp456.23MB

07 Pre-Processing the Data to Apply Methodology/002 Pre-Processing the Data part 1.mp463.08MB

07 Pre-Processing the Data to Apply Methodology/007 Precision and Recall.mp454.53MB

07 Pre-Processing the Data to Apply Methodology/001 Review the Data and the Focus of the Fraudulent Transactions Case.mp479.02MB

01 A Brief Introduction to R and RStudio using Scripts/001 Course Overview.mp47.84MB

01 A Brief Introduction to R and RStudio using Scripts/013 Data Structures Dataframes part 2.mp457.03MB

01 A Brief Introduction to R and RStudio using Scripts/014 Creating New Functions.mp469.69MB

01 A Brief Introduction to R and RStudio using Scripts/005 Factors part 1.mp440.95MB

01 A Brief Introduction to R and RStudio using Scripts/011 Data Structures Lists.mp461.81MB

01 A Brief Introduction to R and RStudio using Scripts/009 Data Structures Matrices and Arrays part 1.mp442.79MB

01 A Brief Introduction to R and RStudio using Scripts/010 Data Structures Matrices and Arrays part 2.mp439.44MB

01 A Brief Introduction to R and RStudio using Scripts/007 Generating Sequences.mp484.51MB

01 A Brief Introduction to R and RStudio using Scripts/004 Data Structures Vectors part 2.mp447.78MB

01 A Brief Introduction to R and RStudio using Scripts/002 Introduction to R for Data Mining.mp487.9MB

01 A Brief Introduction to R and RStudio using Scripts/012 Data Structures Dataframes part 1.mp449.3MB

01 A Brief Introduction to R and RStudio using Scripts/006 Factors part 2.mp451.89MB

01 A Brief Introduction to R and RStudio using Scripts/008 Indexing aka Subscripting or Subsetting.mp441.23MB

01 A Brief Introduction to R and RStudio using Scripts/003 Data Structures Vectors part 1.mp443.78MB

06 Examine the Data in the Fraudulent Transactions Case Study/002 Fraudulent Case Study Introduction.mp411.17MB

06 Examine the Data in the Fraudulent Transactions Case Study/005 Continue Exploring the Data.mp449.26MB

06 Examine the Data in the Fraudulent Transactions Case Study/001 Exercise Solution from Evaluating and Selecting Models.mp419.53MB

06 Examine the Data in the Fraudulent Transactions Case Study/004 Exploring the Data with Eye toward Missingness.mp463.78MB

06 Examine the Data in the Fraudulent Transactions Case Study/003 Prelude to Exploring the Data.mp419.48MB

05 Evaluating and Selecting Models/004 Setting up K-Fold Evaluation part 2.mp454.83MB

05 Evaluating and Selecting Models/003 Setting up K-Fold Evaluation part 1.mp472.19MB

05 Evaluating and Selecting Models/008 Predicting from the Models.mp475.05MB

05 Evaluating and Selecting Models/009 Comparing the Predictions.mp466.94MB

05 Evaluating and Selecting Models/007 Finish Evaluating Models.mp465.73MB

05 Evaluating and Selecting Models/001 Alternative Model Evaluation Criteria.mp476.1MB

05 Evaluating and Selecting Models/006 Best Model part 2.mp455.58MB

05 Evaluating and Selecting Models/002 Introduction to K-Fold Cross-Validation.mp466.04MB

05 Evaluating and Selecting Models/005 Best Model part 1.mp444.43MB

08 Methodology to Find Outliers Fraudulent Transactions/004 Cumulative Recall Chart.mp452.34MB

08 Methodology to Find Outliers Fraudulent Transactions/009 Experimental Methodology to find Outliers part 4.mp463.94MB

08 Methodology to Find Outliers Fraudulent Transactions/001 Exercise from Previous Session.mp412.82MB

08 Methodology to Find Outliers Fraudulent Transactions/003 Review Lift Charts and Precision Recall Curves.mp449.27MB

08 Methodology to Find Outliers Fraudulent Transactions/007 Experimental Methodology to find Outliers part 2.mp470.71MB

08 Methodology to Find Outliers Fraudulent Transactions/005 Creating More Functions for the Experimental Methodology.mp437.96MB

08 Methodology to Find Outliers Fraudulent Transactions/002 Review Precision and Recall.mp448.12MB

08 Methodology to Find Outliers Fraudulent Transactions/006 Experimental Methodology to find Outliers part 1.mp457.49MB

08 Methodology to Find Outliers Fraudulent Transactions/010 Experimental Methodology to find Outliers part 5.mp433.41MB

08 Methodology to Find Outliers Fraudulent Transactions/008 Experimental Methodology to find Outliers part 3.mp467.48MB

02 Inputting and Outputting Data and Text/005 Example Program powers.R.mp448.33MB

02 Inputting and Outputting Data and Text/002 Using the scan Function for Input part 2.mp423.92MB

02 Inputting and Outputting Data and Text/001 Using the scan Function for Input part 1.mp425.08MB

02 Inputting and Outputting Data and Text/003 Using readline, cat and print Functions.mp444MB

02 Inputting and Outputting Data and Text/008 Reading and Writing Files part 2.mp459.2MB

02 Inputting and Outputting Data and Text/004 Using readLines Function and Text Data.mp458.48MB

02 Inputting and Outputting Data and Text/006 Example Program quad2b.R.mp448.33MB

02 Inputting and Outputting Data and Text/007 Reading and Writing Files part 1.mp422.59MB

10 Sidebar on Boosting/004 Replicating Adaboost using Rpart part 2.mp483.57MB

10 Sidebar on Boosting/006 Boosting Exercise.mp444.8MB

10 Sidebar on Boosting/002 Boosting Demo Basics using R.mp451.87MB

10 Sidebar on Boosting/003 Replicating Adaboost using Rpart Recursive Partitioning Package.mp473.06MB

10 Sidebar on Boosting/001 Introduction to Boosting from Rattle course.mp454.25MB

10 Sidebar on Boosting/005 Boosting Extensions and Variants.mp484.89MB

15 Wrap Up Stock Market Case Study/003 Last Session Wrap-Up part 2.mp450.07MB

15 Wrap Up Stock Market Case Study/001 Prologue to Last Session Wrap-Up.mp469.43MB

15 Wrap Up Stock Market Case Study/002 Last Session Wrap-Up part 1.mp460.32MB

11 Introduction to Stock Market Prediction Case Study/004 Accessing the Data part 1.mp453.34MB

11 Introduction to Stock Market Prediction Case Study/010 Defining the Prediction Tasks part 5.mp442.69MB

11 Introduction to Stock Market Prediction Case Study/003 Case Study Background and Data part 2.mp468.39MB

11 Introduction to Stock Market Prediction Case Study/002 Case Study Background and Data part 1.mp469.88MB

11 Introduction to Stock Market Prediction Case Study/001 Introduction to Stock Market Case Study and Materials.mp414.95MB

11 Introduction to Stock Market Prediction Case Study/005 Accessing the Data part 2.mp443.16MB

11 Introduction to Stock Market Prediction Case Study/007 Defining the Prediction Tasks part 2.mp475.3MB

11 Introduction to Stock Market Prediction Case Study/009 Defining the Prediction Tasks part 4.mp443.73MB

11 Introduction to Stock Market Prediction Case Study/006 Defining the Prediction Tasks part 1.mp463.1MB

11 Introduction to Stock Market Prediction Case Study/008 Defining the Prediction Tasks part 3.mp459.8MB

04 Obtaining Prediction Models/003 Examine Alternative Regression Models.mp4104.96MB

04 Obtaining Prediction Models/005 Strategy for Pruning Trees.mp464.89MB

04 Obtaining Prediction Models/002 Creating Prediction Models.mp4106.77MB

04 Obtaining Prediction Models/001 Read in Data Files.mp478MB

04 Obtaining Prediction Models/004 Regression Trees.mp495.94MB

09 The Data Mining Tasks to Find the Fraudulent Transactions/003 Review of Fraud Case part 3.mp455.21MB

09 The Data Mining Tasks to Find the Fraudulent Transactions/001 Review of Fraud Case part 1.mp458.71MB

09 The Data Mining Tasks to Find the Fraudulent Transactions/005 Local Outlier Factors.mp467.57MB

09 The Data Mining Tasks to Find the Fraudulent Transactions/004 Baseline Boxplot Rule.mp438.57MB

09 The Data Mining Tasks to Find the Fraudulent Transactions/009 SMOTE and Naive Bayes part 2.mp451.6MB

09 The Data Mining Tasks to Find the Fraudulent Transactions/007 Supervised and Unsupervised Approaches.mp474.09MB

09 The Data Mining Tasks to Find the Fraudulent Transactions/002 Review of Fraud Case part 2.mp456.72MB

09 The Data Mining Tasks to Find the Fraudulent Transactions/008 SMOTE and Naive Bayes part 1.mp461.38MB

09 The Data Mining Tasks to Find the Fraudulent Transactions/006 Plotting Everything.mp449.78MB

14 Model Evaluation and Selection/001 Quick Review of Case Study Support Vector Machines SVMs.mp455.98MB

14 Model Evaluation and Selection/010 Continue Evaluating part 2.mp462.74MB

14 Model Evaluation and Selection/005 So What Approach is Recommended .mp447.52MB

14 Model Evaluation and Selection/004 Why You Cannot Randomly Resample Records.mp444.75MB

14 Model Evaluation and Selection/011 Continue Evaluating part 3.mp454.33MB

14 Model Evaluation and Selection/003 Evaluating Policy One and Policy Two.mp448.91MB

14 Model Evaluation and Selection/006 Experimental Model Comparisons part 1.mp457.08MB

14 Model Evaluation and Selection/008 Set Up Ranksystems.mp478.29MB

14 Model Evaluation and Selection/002 Begin Evaluating Models.mp471.81MB

14 Model Evaluation and Selection/009 Continue Evaluating part 1.mp455.79MB

14 Model Evaluation and Selection/007 Experimental Model Comparisons part 2.mp462.74MB