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Videos uploaded by user “Rushdi Shams”
Weka Tutorial 05: Held-out Testing (Classification)
 
06:45
Weka machine learning tool has the option to develop a classifier and apply that to your test sets. This tutorial shows you how.
Views: 51961 Rushdi Shams
Weka Tutorial 22: Setting Class Attribute (Data Preprocessing)
 
02:49
This tutorial tells you what to do to take your class feature to the very end of your feature list using Weka Explorer.
Views: 17143 Rushdi Shams
Weka Tutorial 09: Feature Selection with Wrapper (Data Dimensionality)
 
11:03
This tutorial shows you how you can use Weka Explorer to select the features from your feature vector for classification task (Wrapper method)
Views: 63434 Rushdi Shams
Weka Tutorial 04: Systematic Oversampling (Class Imbalance Problem)
 
12:43
Are you facing class imabalance problem? Well, this tutorial demonstrates how you can oversample to solve it!
Views: 63464 Rushdi Shams
Weka Tutorial 35: Creating Training, Validation and Test Sets (Data Preprocessing)
 
10:10
The tutorial that demonstrates how to create training, test and cross validation sets from a given dataset.
Views: 70056 Rushdi Shams
Weka Tutorial 28: ROC Curves and AUC (Model Evaluation)
 
06:44
This tutorial demonstrates how to produce a single ROC curve for a single classifier. It also demonstrates how to get the Area under ROC curve or (AUC). ROC curves are cost-sensitive measures to evaluate classifier performance. However, it is not a good mesure of model goodness if the dataset is imbalanced (highly skewed class distributions are present). LinkedIn: http://www.linkedin.com/pub/rushdi-shams/3b/83b/9b3
Views: 70167 Rushdi Shams
Weka Tutorial 24: Model Comparison (Model Evaluation)
 
11:19
In this tutorial, you will learn how to use Weka Experimenter to compare the performances of multiple classifiers on single or multiple datasets. Please subscribe to get more updates and like if the tutorial is useful. Link in: http://www.linkedin.com/pub/rushdi-shams/3b/83b/9b3
Views: 26396 Rushdi Shams
Weka Tutorial 20: Attribute Selection with Knowledge Flow Environment (Data Dimensionality)
 
04:46
How to use knowledge flow environment to get the attributes selected by wrapper method.
Views: 12241 Rushdi Shams
Weka Tutorial 33: Random Undersampling (Class Imbalance Problem)
 
03:58
The tutorial demonstrates how to undersample the majority class in Weka so that the number of instances in each class becomes exactly the same. Random undersampling (RUS) is a popular method to overcome class imbalance problems. For further readings: http://en.wikipedia.org/wiki/Oversampling_and_undersampling_in_data_analysis
Views: 12904 Rushdi Shams
Weka Tutorial 02: Data Preprocessing 101 (Data Preprocessing)
 
10:42
This tutorial demonstrates various preprocessing options in Weka. However, details about data preprocessing will be covered in the upcoming tutorials.
Views: 155217 Rushdi Shams
Weka Tutorial 06: Discretization (Data Preprocessing)
 
03:53
An important feature of Weka is Discretization where you group your feature values into a defined set of interval values. Experiments showed that algorithms like Naive Bayes works well with discretized feature values
Views: 55062 Rushdi Shams
Apache Solr Tutorial 1: Download and Install
 
07:32
- To download Solr 4.10.2: http://www.apache.org/dyn/closer.cgi/lucene/solr/4.10.2 Then unzip the pack anywhere. You need Java 7 at least. - To run Solr: cd solr/example/ java -jar start.jar [The port no. is 8983]
Views: 44330 Rushdi Shams
Weka Tutorial 31: Document Classification 1 (Application)
 
12:04
This tutorial demonstrates the use of an unsupervised attribute filter called StringtoWordVector. This filter converts the strings (texts) of your document into a vector of words. Then using the word vectors, you can develop a classification model. The next tutorial shows the actual work involved in document classification
Views: 23654 Rushdi Shams
Weka Tutorial 39: Cost Sensitive Learning (Classification)
 
09:59
This video describes how to use cost sensitive learning which is useful for imbalanced datasets.
Views: 8485 Rushdi Shams
Weka Tutorial 36: Learning Curve 1 (Model Evaluation)
 
11:06
This video demonstrates how to produce learning curves in Weka. Learning curves can be produced in two common ways: (1) By varying data (2) By varying model parameters. This tutorial shows how to produce learning curves for a classifier by varying the amount of data.
Views: 13607 Rushdi Shams
Weka Tutorial 30: Multiple ROC Curves (Model Evaluation)
 
10:19
ROC curves produced from different classifiers are a good means to compare classifier performances. This session demonstrates the use of Knowledge-flow environment of Weka to generate multiple ROC curves for more than one classifiers. Tutorial 28 shows how to generate a single ROC curve for a single classifier using Weka Explorer. The tutorial can be found at http://www.youtube.com/watch?v=j97h_-b0gvw
Views: 21634 Rushdi Shams
Weka Tutorial 29: Precision-Recall Curve (Model Evaluation)
 
04:27
Precision-recall curves are important to visualize your classifier performances. The goal is to observe whether your precision-recall curve is towards the upper right corner of the chart. P-R curve is especially important to observe model quality if your dataset has class imbalance problems.
Views: 19064 Rushdi Shams
Apache Solr Tutorial 6: Delete/Remove/Clean Index
 
03:35
Other Solr tutorials: https://www.youtube.com/watch?v=uX7jV74oy1w https://www.youtube.com/watch?v=YDYBORUYAXU https://www.youtube.com/watch?v=Zh_aYQkG0Wc http://youtu.be/HBx98mf1M8s http://youtu.be/UvnbcyZYsGE This short tutorial shows how to remove/clean/delete the indexes that you create with Apache Solr
Views: 7796 Rushdi Shams
Weka Tutorial 32: Document classification 2 (Application)
 
12:32
The tutorial demonstrates how you can classify documents using Weka's String to Word vector attribute filter. The tutorial has a preceding tutorial that demonstrates the used of the filter in detail and can be found at http://www.youtube.com/watch?v=jSZ9jQy1sfE
Views: 17195 Rushdi Shams
Weka Tutorial 01: ARFF 101 (Data Preprocessing)
 
06:58
Weka Machine Learning Tutorial on how to prepare an arff file
Views: 190271 Rushdi Shams
Weka Tutorial 10: Feature Selection with Filter (Data Dimensionality)
 
11:09
This tutorial shows how to select features from a set of features that performs best with a classification algorithm using filter method.
Views: 64251 Rushdi Shams
Weka Tutorial 03: Classification 101 using Explorer (Classification)
 
14:58
In this tutorial, classification using Weka Explorer is demonstrated. This is the very basic tutorial where a simple classifier is applied on a dataset in a 10 Fold CV. For more variations of classification, watch out other tutorials on this channel.
Views: 144627 Rushdi Shams
Weka Tutorial 12: Cross Validation Error Rates (Model Evaluation)
 
08:32
In this tutorial, Weka experimenter is used to find out the error rates of every iteration in a k-fold setup. These error rates for every iteration is required to find out overfitting, best performing classification model and mostly to find out the statistical significance test for k-fold setup.
Views: 18538 Rushdi Shams
Weka Tutorial 08: Numeric Transform (Data Preprocessing)
 
07:06
Weka provides a filter called NumericTransform so that you can use the Java.Lang.Math class methods to transform your feature values. This is particularly useful as for some classification algorithms you will see that they perform better with integer values than real numbers or vice versa.
Views: 29274 Rushdi Shams
Apache Solr Tutorial 5: Complex Query Format
 
05:55
Other Solr tutorials: https://www.youtube.com/watch?v=uX7jV74oy1w https://www.youtube.com/watch?v=YDYBORUYAXU https://www.youtube.com/watch?v=Zh_aYQkG0Wc http://youtu.be/HBx98mf1M8s This tutorial demonstrates how you can post complex query using fl, group, sort, group.field, group.main, facet, facet.field parameters. The query used in this tutorial and its explanation is as follows: http://localhost:8983/solr/query?q=*:*&fl=id,title,series_s,pubyear_i&sort=pubyear_i+desc&group=true&group.field=series_s&group.main=true&facet=true&facet.field=cat q=*:* the main query, *:* matches all documents fl=id,title,series_s,pubyear_i field list – the list of fields we want to return for matching documents sort=pubyear_i desc sorts the list of matching documents by pubyear_i in descending order group=true turns on the grouping / field-collapsing feature group.main=true put the grouped documents where the main query results normally appear instead of in the grouped section of the response. group.field=series_s group together matching documents by the series_s field facet=true turns on the faceting feature facet.field=cat get facet counts for each value of the cat field. In this example, we have 5 “fantasy” books and 4 “sci-fi” books that match the query
Views: 13939 Rushdi Shams
Weka Tutorial 15: Java API 101 (Application)
 
10:10
In this tutorial, I showed how to interact with the Weka API for the first time with a simple Java code. In this code, I have loaded an ARFF file called 2.arff and then used Naive Bayes classifier with a 10 fold CV setup. I showed the standard output of Weka on the Eclipse output as well as the F-score, precision and recall of the 10 fold CV.
Views: 50376 Rushdi Shams
Weka Tutorial 27: Inverse k-fold Cross Validation (Model Evaluation)
 
05:55
This video demonstrates how to do inverse k-fold cross validation.
Views: 9771 Rushdi Shams
Weka Tutorial 14: The Java API with Eclipse (Application)
 
07:38
In this tutorial I showed how you can download and incorporate the Weka API with Eclipse Java IDE. The download link for the api is http://www.cs.waikato.ac.nz/ml/weka/
Views: 36729 Rushdi Shams
Weka Tutorial 13: Stacking Multiple Classifiers (Classification)
 
08:52
In this tutorial I have shown how to use Weka for combining multiple classification algorithms. Both ensembles (bagging and boosting) and voting combining technique are discussed. The parameters and procedure to invoke stacking is left for the user because it is closely related to voting.
Views: 31923 Rushdi Shams
Apache Solr Tutorial 2: Installing CURL
 
04:11
- To install CURL: sudo apt-get install curl - If you get error (curl: error while loading shared libraries: libcurl.so.4: cannot open shared object file: No such file or directory) while running CURL: ln -s /usr/local/lib/libcurl.so.4 /usr/lib/libcurl.so.4
Views: 15257 Rushdi Shams
Java- HashMap and TreeMap
 
13:21
How to create, populate and iterate HashMap and TreeMap in Java
Views: 27086 Rushdi Shams
Weka Tutorial 19: Outliers and Extreme Values (Data Preprocessing)
 
16:35
This tutorial shows how to detect and remove outliers and extreme values from datasets using WEKA.
Views: 31166 Rushdi Shams
Weka Tutorial 34: Generating Stratified Folds (Data Preprocessing)
 
04:49
This tutorial demonstrates how to generate stratified folds from your dataset. Stratification is extremely important for cross validation where you need to create X number of folds from your dataset and the data distribution in each fold should be close to that in the entire dataset. For more information on stratification: http://en.wikipedia.org/wiki/Stratified_sampling
Views: 6768 Rushdi Shams
Apache Solr Tutorial 4: Indexing CSV Data
 
07:13
This tutorial demonstrates how you can provide data in the CSV format to solr for indexing. It also demonstrates how to make customized query to solr. - To add books using CSV: curl http://localhost:8983/solr/update?commitWithin=5000 -H 'Content-type:text/csv' -d ' id,cat,pubyear_i,title,author,series_s,sequence_i book2,fantasy,1996,A Game of Thrones,George R.R. Martin,A Song of Ice and Fire,1 book3,fantasy,1999,A Clash of Kings,George R.R. Martin,A Song of Ice and Fire,2 book4,sci-fi,1951,Foundation,Isaac Asimov,Foundation Series,1 book5,sci-fi,1952,Foundation and Empire,Isaac Asimov,Foundation Series,2 book6,sci-fi,1992,Snow Crash,Neal Stephenson,Snow Crash, book7,sci-fi,1984,Neuromancer,William Gibson,Sprawl trilogy,1 book8,fantasy,1985,The Black Company,Glen Cook,The Black Company,1 book9,fantasy,1965,The Black Cauldron,Lloyd Alexander,The Chronicles of Prydain,2 ' - To display books with title "black": http://localhost:8983/solr/query?q=title:black&fl=author,title
Views: 16190 Rushdi Shams
Apache Solr Tutorial 7: Configuring a Single Solr Core (1/3)
 
12:43
In this tutorial I demonstrated how to configure a Solr core. This is a three part tutorial where the first two parts demonstrate how to configure a Solr core and the last part shows how to use that core for data indexing. https://www.youtube.com/watch?v=uX7jV74oy1w https://www.youtube.com/watch?v=YDYBORUYAXU https://www.youtube.com/watch?v=Zh_aYQkG0Wc http://youtu.be/HBx98mf1M8s http://youtu.be/UvnbcyZYsGE http://youtu.be/W2mx7WQDJbE
Views: 19310 Rushdi Shams
Weka Tutorial 37: Weighted Averages of Scores (Model Evaluation)
 
05:22
An interesting performance measure that Weka gives is the Weighted average of TP rate, FP rate, Precision, Recall, F-measure, ROC area and so on. But this can be confusing at some times, especially for weighted average F-measure, which is not actually the harmonic mean of the weighted average precision and recall. How does then Weka calculate the weighted average F-measure (and others)? This tutorial clearly and quantitatively answers that!
Views: 7687 Rushdi Shams
Apache Solr Tutorial 8: Configuring a Single Solr Core (2/3)
 
17:17
In this tutorial I demonstrated how to configure a Solr core. This is a three part tutorial where the first two parts demonstrate how to configure a Solr core and the last part shows how to use that core for data indexing. Other Tutorials on Solr: https://www.youtube.com/watch?v=uX7jV74oy1w https://www.youtube.com/watch?v=YDYBORUYAXU https://www.youtube.com/watch?v=Zh_aYQkG0Wc http://youtu.be/HBx98mf1M8s http://youtu.be/UvnbcyZYsGE http://youtu.be/W2mx7WQDJbE http://youtu.be/-f0NugqSnms
Views: 10568 Rushdi Shams
Weka Tutorial 17: Saving Results in Weka (Application)
 
05:32
In this tutorial, I showed how the results produced by Weka can be saved with the Experimenter application.
Views: 16936 Rushdi Shams
Weka Tutorial 11: Generating Non-stratified Folds (Data Preprocessing)
 
05:35
This tutorial shows you how to get the folds from a k-fold setup (Both stratified and un-stratified)
Views: 12833 Rushdi Shams
Apache Solr Tutorial 3: Indexing JSON Data
 
11:02
- To index a book with id book1: curl http://localhost:8983/solr/update -H 'Content-type:application/json' -d ' [ {"id" : "book1", "title" : "American Gods", "author" : "Neil Gaiman" } ]' - To display the book information using curl: curl http://localhost:8983/solr/get?id=book1 - To display the book information using url: http://localhost:8983/solr/get?id=book1 - Updating the book information: curl http://localhost:8983/solr/update -H 'Content-type:application/json' -d ' [ {"id" : "book1", "cat" : { "add" : "fantasy" }, "pubyear_i" : { "add" : 2001 }, "ISBN_s" : { "add" : "0-380-97365-0"} } ]' - To display the updated book information using curl again: curl http://localhost:8983/solr/get?id=book1
Views: 23387 Rushdi Shams
Weka Tutorial 38: Learning Curves 2 (Model Evaluation)
 
07:39
This video demonstrates how to produce learning curves in Weka. Learning curves can be produced in two common ways: (1) By varying data (2) By varying model parameters. This tutorial shows how to produce learning curves for a classifier by varying the parameters of a learning algorithm.
Views: 5776 Rushdi Shams
Weka Tutorial 18: Classification 101 with Knowledge Flow Environment (Classification)
 
16:59
This tutorial shows the introduction with the Weka knowledge flow environment
Views: 24032 Rushdi Shams
Weka Tutorial 23: Classification 101 using API (Classification)
 
09:37
This tutorial shows how to train a classifier on data using the Java API
Views: 16216 Rushdi Shams
Weka Tutorial 07: Models 101 (Model Evaluation)
 
04:55
If you use 10 fold CV in Weka, then on the result pane, all you see is the average results of 10 different models on 10 different folds. But after that, Weka deletes all of these models. So, if you save the model you built from 10 fold CV, then this is the exact same model if you had chosen "Use training set". Remember: If you use 10 fold CV and save that model, then it is neither the best performing model nor the average of 10 models rather it is the model created using the entire training set.
Views: 24508 Rushdi Shams
Apache Solr Tutorial 9: Configuring a Single Solr Core (3/3)
 
08:21
In this tutorial I demonstrated how to configure a Solr core. This is a three part tutorial where the first two parts demonstrate how to configure a Solr core and the last part shows how to use that core for data indexing.
Views: 6793 Rushdi Shams
Weka Tutorial 26: Semi-supervised Learning (Learning Techniques)
 
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This tutorial demonstrates how semi-supervised learning algorithms can be used in Weka. I demonstrate it by using the semi-supervised version of Weka that can be downloaded from http://www.scms.waikato.ac.nz/~fracpete/projects/collective-classification/
Views: 11843 Rushdi Shams
এক যে ছিলো সি ৩ঃ Algorithm and Pseudocode
 
11:08
Programming Tutorial C 3: Algorithm and Pseudocode (Bangla) http://youtu.be/wh8IcjHvadQ http://youtu.be/9HoQYOt_zoQ
Views: 4782 Rushdi Shams
Weka Tutorial 16: Detail Cross Validation Results using API (Model Evaluation)
 
11:09
In this tutorial, I showed how to use Weka API to get the results of every iteration in a K-fold cross validation setup. Look at tutorial 12 where I used Experimenter to do the same job.
Views: 12611 Rushdi Shams
Weka Tutorial 21: Merge and Append ARFF files (Data Preprocessing)
 
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This tutorial shows how to append and merge 2 or more than 2 ARFF files
Views: 14473 Rushdi Shams
এক যে ছিলো সি ৫: Increment and Decrement Operator
 
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Programming Tutorial C 5: Increment and Decrement Operator (Bangla) Other tutorials on C: http://youtu.be/wh8IcjHvadQ http://youtu.be/9HoQYOt_zoQ http://youtu.be/Os_VulEjGXM http://youtu.be/VkpLgT3rhZc
Views: 1435 Rushdi Shams