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Search results “Classification in data mining using weka api”
WEKA API 14/19: Making Predictions (Classification)
 
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To access the code go to the Machine Learning Tutorials Section on the Tutorials page here: http://www.brunel.ac.uk/~csstnns Using WEKA in java
Views: 19634 Noureddin Sadawi
Weka Tutorial 03: Classification 101 using Explorer (Classification)
 
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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: 160459 Rushdi Shams
Weka Tutorial 23: Classification 101 using API (Classification)
 
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This tutorial shows how to train a classifier on data using the Java API
Views: 17385 Rushdi Shams
Weka classifier from Java
 
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Final proyect, using classifier on diabetes dataset. Authors: Oyervide Jonnathan & Poveda Adrian
Views: 6405 Adrian Poveda
Weka Tutorial 02: Data Preprocessing 101 (Data Preprocessing)
 
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This tutorial demonstrates various preprocessing options in Weka. However, details about data preprocessing will be covered in the upcoming tutorials.
Views: 173932 Rushdi Shams
WEKA API 12/19: Model Evaluation
 
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To access the code go to the Machine Learning Tutorials Section on the Tutorials page here: http://www.brunel.ac.uk/~csstnns Using WEKA in java
Views: 6203 Noureddin Sadawi
WEKA API 9/19: Classifiers in WEKA
 
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To access the code go to the Machine Learning Tutorials Section on the Tutorials page here: http://www.brunel.ac.uk/~csstnns Using WEKA in java
Views: 9831 Noureddin Sadawi
How to Implement Naïve Bayes Algorithm In Weka Tool
 
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Hii there from Codegency! We are a team of young software developers and IT geeks who are always looking for challenges and ready to solve them, Feel free to contact us.. Do visit my instagram page and also like us on facebook, stay connected :) Instagram: https://www.instagram.com/code_gency/ Facebook: https://www.facebook.com/cgency/ Twitter : https://www.twitter.com/codegency Contact: +919769620035, +918108849398 For Blackbook Writeups & Descriptions: https://codegency.blogspot.in For Latest Notes & References: https://sites.google.com/view/itscholar/home
Views: 2648 Codegency
Data Mining with Weka (4.4: Logistic regression)
 
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Data Mining with Weka: online course from the University of Waikato Class 4 - Lesson 4: Logistic regression http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/augc8F https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 33891 WekaMOOC
Data Mining with Weka (4.3: Classification by regression)
 
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Data Mining with Weka: online course from the University of Waikato Class 4 - Lesson 3: Classification by regression http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/augc8F https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 29266 WekaMOOC
Weka Tutorial 14: The Java API with Eclipse (Application)
 
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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: 39002 Rushdi Shams
Weka Tutorial: Bayesian Classification, Nearest Neighbor, K means Clustering
 
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Demonstrating how to do Bayesian Classification, Nearest Neighbor, K means Clustering using WEKA . Generating data set and Probability Density Function using MATLAB. Important links: To know more about .arff formats go to: http://www.cs.waikato.ac.nz/ml/weka/arff.html Data sets: http://repository.seasr.org/Datasets/UCI/arff/ Online matlab: http://octave-online.net/
Views: 33340 Niranjan Singh
WEKA API 7/19: Attribute Selection
 
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To access the code go to the Machine Learning Tutorials Section on the Tutorials page here: http://www.brunel.ac.uk/~csstnns Using WEKA in java
Views: 11432 Noureddin Sadawi
Weka Tutorial 15: Java API 101 (Application)
 
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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: 53283 Rushdi Shams
Text Classification with Weka using a J48 Decision Tree
 
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In this tutorial it is described how to train a J48 decision tree classifier to classify certain sentences into three different classes. Afterwords we save this classification model in order to use it for a different testing set of sentences. While doing so, the most important informations displayed in the plaintext output are explained. Follow me on Twitter: https://twitter.com/PhilOver_
Views: 48799 S0naris
weka j48 classification tutorial
 
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This is a tutorial for the Innovation and technology course in the ePC-UCB. La Paz Bolivia
Views: 56205 Alejandro Peña
Prediction Using Weka Tool- Machine Learning Tutorial
 
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Weka is an Open source Machine Learning Application which helps to predict the required data as per the given parameters
Views: 7405 MOHIT RATNESH
Document Classification in Weka
 
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A couple ways to do document classification in Weka. Data was taken from Trump's tweets, which you can find (with device info) at http://www.trumptwitterarchive.com/archive
Views: 2091 jengolbeck
Naive Bayes w/ JAVA - Tutorial 01
 
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Website + download source code @ http://www.zaneacademy.com
Views: 7366 zaneacademy
Weka Text Classification for First Time & Beginner Users
 
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59-minute beginner-friendly tutorial on text classification in WEKA; all text changes to numbers and categories after 1-2, so 3-5 relate to many other data analysis (not specifically text classification) using WEKA. 5 main sections: 0:00 Introduction (5 minutes) 5:06 TextToDirectoryLoader (3 minutes) 8:12 StringToWordVector (19 minutes) 27:37 AttributeSelect (10 minutes) 37:37 Cost Sensitivity and Class Imbalance (8 minutes) 45:45 Classifiers (14 minutes) 59:07 Conclusion (20 seconds) Some notable sub-sections: - Section 1 - 5:49 TextDirectoryLoader Command (1 minute) - Section 2 - 6:44 ARFF File Syntax (1 minute 30 seconds) 8:10 Vectorizing Documents (2 minutes) 10:15 WordsToKeep setting/Word Presence (1 minute 10 seconds) 11:26 OutputWordCount setting/Word Frequency (25 seconds) 11:51 DoNotOperateOnAPerClassBasis setting (40 seconds) 12:34 IDFTransform and TFTransform settings/TF-IDF score (1 minute 30 seconds) 14:09 NormalizeDocLength setting (1 minute 17 seconds) 15:46 Stemmer setting/Lemmatization (1 minute 10 seconds) 16:56 Stopwords setting/Custom Stopwords File (1 minute 54 seconds) 18:50 Tokenizer setting/NGram Tokenizer/Bigrams/Trigrams/Alphabetical Tokenizer (2 minutes 35 seconds) 21:25 MinTermFreq setting (20 seconds) 21:45 PeriodicPruning setting (40 seconds) 22:25 AttributeNamePrefix setting (16 seconds) 22:42 LowerCaseTokens setting (1 minute 2 seconds) 23:45 AttributeIndices setting (2 minutes 4 seconds) - Section 3 - 28:07 AttributeSelect for reducing dataset to improve classifier performance/InfoGainEval evaluator/Ranker search (7 minutes) - Section 4 - 38:32 CostSensitiveClassifer/Adding cost effectiveness to base classifier (2 minutes 20 seconds) 42:17 Resample filter/Example of undersampling majority class (1 minute 10 seconds) 43:27 SMOTE filter/Example of oversampling the minority class (1 minute) - Section 5 - 45:34 Training vs. Testing Datasets (1 minute 32 seconds) 47:07 Naive Bayes Classifier (1 minute 57 seconds) 49:04 Multinomial Naive Bayes Classifier (10 seconds) 49:33 K Nearest Neighbor Classifier (1 minute 34 seconds) 51:17 J48 (Decision Tree) Classifier (2 minutes 32 seconds) 53:50 Random Forest Classifier (1 minute 39 seconds) 55:55 SMO (Support Vector Machine) Classifier (1 minute 38 seconds) 57:35 Supervised vs Semi-Supervised vs Unsupervised Learning/Clustering (1 minute 20 seconds) Classifiers introduces you to six (but not all) of WEKA's popular classifiers for text mining; 1) Naive Bayes, 2) Multinomial Naive Bayes, 3) K Nearest Neighbor, 4) J48, 5) Random Forest and 6) SMO. Each StringToWordVector setting is shown, e.g. tokenizer, outputWordCounts, normalizeDocLength, TF-IDF, stopwords, stemmer, etc. These are ways of representing documents as document vectors. Automatically converting 2,000 text files (plain text documents) into an ARFF file with TextDirectoryLoader is shown. Additionally shown is AttributeSelect which is a way of improving classifier performance by reducing the dataset. Cost-Sensitive Classifier is shown which is a way of assigning weights to different types of guesses. Resample and SMOTE are shown as ways of undersampling the majority class and oversampling the majority class. Introductory tips are shared throughout, e.g. distinguishing supervised learning (which is most of data mining) from semi-supervised and unsupervised learning, making identically-formatted training and testing datasets, how to easily subset outliers with the Visualize tab and more... ---------- Update March 24, 2014: Some people asked where to download the movie review data. It is named Polarity_Dataset_v2.0 and shared on Bo Pang's Cornell Ph.D. student page http://www.cs.cornell.edu/People/pabo/movie-review-data/ (Bo Pang is now a Senior Research Scientist at Google)
Views: 139419 Brandon Weinberg
How to use WEKA software for data mining tasks
 
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In this video, I'll guide you how to use WEKA software for preprocessing, classifying, clustering, association. WEKA is a collection of machine learning algorithms for performing data mining tasks. #RanjiRaj #WEKA #DataMining Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj Get WEKA from here : http://www.cs.waikato.ac.nz/ml/weka/
Views: 20889 Ranji Raj
Prediction of Student Results #Data Mining
 
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We used WEKA datamining s-w which yields the result in a flash.
Views: 34246 GRIETCSEPROJECTS
Weka Data Mining Tutorial for First Time & Beginner Users
 
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23-minute beginner-friendly introduction to data mining with WEKA. Examples of algorithms to get you started with WEKA: logistic regression, decision tree, neural network and support vector machine. Update 7/20/2018: I put data files in .ARFF here http://pastebin.com/Ea55rc3j and in .CSV here http://pastebin.com/4sG90tTu Sorry uploading the data file took so long...it was on an old laptop.
Views: 471610 Brandon Weinberg
API de weka en java
 
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Como importar la API de weka en Java
Views: 1824 jjalamo
Advanced Data Mining with Weka (2.5: Classifying tweets)
 
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Advanced Data Mining with Weka: online course from the University of Waikato Class 2 - Lesson 5: Classifying tweets http://weka.waikato.ac.nz/ Slides (PDF): https://goo.gl/4vZhuc https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 4360 WekaMOOC
Weka Tutorial 35: Creating Training, Validation and Test Sets (Data Preprocessing)
 
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The tutorial that demonstrates how to create training, test and cross validation sets from a given dataset.
Views: 81443 Rushdi Shams
Weka Tutorial 24: Model Comparison (Model Evaluation)
 
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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: 31307 Rushdi Shams
The OneR Classifier .. What it is and How it Works
 
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My web page: www.imperial.ac.uk/people/n.sadawi
Views: 31585 Noureddin Sadawi
Classification and Prediction algorithms in WEKA
 
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1. Generating and preparing data 2. Importing .csv file into weka 3. Applying different classification algorithms (ZeroR, SVM and J48) to train a model Watch video for more details. Watch and subscribe our official channel and pages. Our Blog :: http://coding-guru.com/ Our Facebook Page :: https://www.facebook.com/codingguruz/ Our Google ++ Page :: https://plus.google.com/u/0/b/100901910873665781089/+Codinggurus
Views: 1145 Coding Guru
Data Mining with Weka (3.6: Nearest neighbor)
 
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Data Mining with Weka: online course from the University of Waikato Class 3 - Lesson 6: Nearest neighbor http://weka.waikato.ac.nz/ Slides (PDF): https://goo.gl/YjZnrh https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 47806 WekaMOOC
Text Classification Using WEKA Part 1
 
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this video is about introducing how can we classify a group of text into 3 main categories: Positive, Negative and Neutral Classes by using WEKA tool
Views: 5669 Ahmed Abdelaziz
Data Mining with Weka (3.3: Using probabilities)
 
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Data Mining with Weka: online course from the University of Waikato Class 3 - Lesson 3: Using probabilities http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/1LRgAI https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 27999 WekaMOOC
More Data Mining with Weka (2.2: Supervised discretization and the FilteredClassifier)
 
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More Data Mining with Weka: online course from the University of Waikato Class 2 - Lesson 2: Supervised discretization and the FilteredClassifier http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/QldvyV https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 11353 WekaMOOC
WEKA API 10/19: Filtered Classifiers in WEKA
 
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To access the code go to the Machine Learning Tutorials Section on the Tutorials page here: http://www.brunel.ac.uk/~csstnns Using WEKA in java
Views: 5395 Noureddin Sadawi
WEKA API 2/19: Loading and Saving Data
 
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To access the code go to the Machine Learning Tutorials Section on the Tutorials page here: http://www.brunel.ac.uk/~csstnns Using WEKA in java
Views: 21493 Noureddin Sadawi
WEKA API 11/19: Regression in WEKA
 
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To access the code go to the Machine Learning Tutorials Section on the Tutorials page here: http://www.brunel.ac.uk/~csstnns Using WEKA in java
Views: 5122 Noureddin Sadawi
More Data Mining with Weka (4.2: The Attribute Selected Classifier)
 
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More Data Mining with Weka: online course from the University of Waikato Class 4 - Lesson 2: The Attribute Selected Classifier http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/I4rRDE https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 12087 WekaMOOC
First time Weka Use : How to create & load data set in Weka : Weka Tutorial # 2
 
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This video will show you how to create and load dataset in weka tool. weather data set excel file https://eric.univ-lyon2.fr/~ricco/tanagra/fichiers/weather.xls
Views: 44461 HowTo
WEKA API 6/19: Discretizing Attributes
 
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To access the code go to the Machine Learning Tutorials Section on the Tutorials page here: http://www.brunel.ac.uk/~csstnns Using WEKA in java
Views: 7252 Noureddin Sadawi
Predicting Target variable Values in Decision Tree Using Weka
 
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Hi Everyone, We usually create a data model but we restrict ourselves till the model creation but we actually don't predict the future values. This video is about how you can predict the target variable values in decision tree. I have used Weka for this implementation. The data set i have used is "Vote" dataset which comes along with Weka. I create 2 data sets - one was Training data set without last 30 rows, and Test data set with last 30 rows but no values for target variable. You can create test data set with "?" implanted for target values in test set.
Views: 5114 Nitin Paighowal
Tutorial on K Means Clustering using Weka
 
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Tutorial on how to apply K-Means using Weka on a data set
Views: 19027 Jyothi Rao
WEKA API 4/19: Filtering Attributes
 
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To access the code go to the Machine Learning Tutorials Section on the Tutorials page here: http://www.brunel.ac.uk/~csstnns Using WEKA in java
Views: 13652 Noureddin Sadawi
Weka Tutorial 05: Held-out Testing (Classification)
 
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Weka machine learning tool has the option to develop a classifier and apply that to your test sets. This tutorial shows you how.
Views: 54898 Rushdi Shams
WEKA API 15/19: Making Predictions (Regression)
 
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To access the code go to the Machine Learning Tutorials Section on the Tutorials page here: http://www.brunel.ac.uk/~csstnns Using WEKA in java
Views: 8350 Noureddin Sadawi
More Data Mining with Weka (2.5: Evaluating 2‐class classification)
 
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More Data Mining with Weka: online course from the University of Waikato Class 2 - Lesson 5: Evaluating 2‐class classification http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/QldvyV https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 7513 WekaMOOC
Weka Tutorial 18: Classification 101 with Knowledge Flow Environment (Classification)
 
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This tutorial shows the introduction with the Weka knowledge flow environment
Views: 25895 Rushdi Shams
More Data Mining with Weka (3.6: Evaluating clusters)
 
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More Data Mining with Weka: online course from the University of Waikato Class 3 - Lesson 6: Evaluating clusters http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/nK6fTv https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 22624 WekaMOOC