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Questions tagged [weka]

Weka (Waikato Environment for Knowledge Analysis) is a collection of machine learning algorithms for data mining tasks.

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41
votes
1answer
50k views

How to interpret error measures?

I am running the classify in Weka for a certain dataset and I've noticed that if I'm trying to predict a nominal value the output specifically shows the correctly and incorrectly predicted values. ...
10
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4answers
4k views

Classifier for uncertain class labels

Let's say I have a set of instances with class labels associated. It does not matter how these instances were labelled, but how certain their class membership is. Each instancs belongs to exactly one ...
9
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1answer
5k views

Principal Component Analysis Vs Feature Selection

I am doing a machine learning project using WEKA. It is a supervised classification and in my basic experiments, I achieved very poor level of accuracy. Then my intention was to do a feature selection,...
7
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2answers
2k views

Interactive decision trees

I was wondering if there is a free tool to build a decision tree in interactive fashion like in SAS Enterprise Mining. I'm used to work with Weka. But nothing fits to my needs. I would like that ...
6
votes
1answer
10k views

How to interpret Weka Logistic Regression output?

Please help interpret results of logistic regression produced by weka.classifiers.functions.Logistic from the WEKA library. I use numeric data from WEKA examples: ...
6
votes
1answer
6k views

How to decide which decision tree classifier to use?

I am confused about which decision tree algorithm in weka to use for my application. I have 5 real input variables and 2 classes. In various online tutorials J48 (C 4.5) seems to be the algorithm of ...
6
votes
3answers
4k views

Data mining classification competition

I'm currently taking a data mining class, and for one our projects we're required to predict the class label for an unknown data set by first building a classifier on a training data set which already ...
6
votes
2answers
755 views

Is cross-validation an effective approach for feature/model selection for microarray data?

I've been working with WEKA to build class predictors using this (rather old..) breast cancer dataset. The dataset is divided into a training and a test set. I've been testing different learning ...
5
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1answer
306 views

What is the right attitude toward open source machine learning toolkits?

There are lots of machine learning toolkits nowadays, such as weka, sklearn, R libs. If we choose to use these toolkits, besides that it is convenient, sometimes ...
5
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1answer
803 views

Interpretation of a one cluster solution using the EM cluster algorithm

I'm trying to use the EM cluster algorithm, provided by the software Weka, to classify my data and it only finds one cluster. Could I interpret this as there are no ways to distinguish the instances ...
4
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1answer
1k views

Unsupervised Random Forest using Weka

I am having some issues understanding how unsupervised Random Forest works according to Breiman. I only have unlabeled data, so the thought arose to use unsupervised Random Forest and use the ...
4
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1answer
1k views

Random forest parameters

I'm trying to make decisions regarding Random forest parameters for classification. My dataset contains 26 features and 6300 instances. How can I decide the values of (the number of trees, number of ...
4
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2answers
307 views

Sweeping across multiple classifiers and choosing the best?

I'm using Weka to perform classification, clustering, and some regression on a few large data sets. I'm currently trying out all the classifiers (decision tree, SVM, naive bayes, etc.). Is there an ...
4
votes
1answer
1k views

Optimizing for target metrics in Weka

I'm a PhD student in Information Retrieval with some limited experience in ML. We've been working on a binary classification task with weka (I'm using weka programmatically via Java), specifically ...
4
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1answer
2k views

Unbalanced dataset - ROC curve to compare classifiers?

I use the machine learning software WEKA for data mining on biological data. I would describe my dataset as unbalanced: It comprises around 2000 instances, ...
3
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2answers
2k views

Methods for comparing clustering results

I am doing an unsupervised clustering analysis for a genomics project. This means that I do not know when a particular clustering analysis is good or not. I am running different clustering algorithms ...
3
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2answers
382 views

Is it possible to build a more “controllable” decision tree like below?

I have 2 real and 1 discrete input variable whereas the output variable takes either of the 2 nominal values (i.e. 2 class problem). First I used Weka to train C 4.5 decision tree in a 10-fold cross ...
3
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2answers
13k views

SVM and SMO main differences

I am unable to clearly see the main differences between SVM & SMO. While I get the fact that SMO provides better algorithm for QP solvers but I see that when I use this in Weka on my MacBook it ...
3
votes
1answer
5k views

30% difference on accuracy between cross-validation and testing with a test set in weka? is it normal?

I'm new with weka and I have a problem with my text classification project using it. I have a train dataset with 1000 instances and one of 200 for testing. The problem is that when I try to test the ...
3
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3answers
6k views

Clustering with Weka

I have to analyse a data set with weka clustering, using 3 clustering algorithms and I need to provide a comparison between them about their performance and suitability. The comparison may include a ...
3
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1answer
1k views

Obtaining R pec survival patient risk percentage

Introduction I have a 300,000-row cancer dataset with around 60 variables (cancer stage, year of diagnosis, radiation therapy, histology, etc.) with a time variable ("number of months survived") and ...
3
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2answers
6k views

WEKA: Visualize combined trees of random forest classifier

I have a small data set consisting of 385 entries and around 200 attributes. Because I want to apply attribute selection and because of the limited size of my data set, I got the advice to use the ...
3
votes
2answers
599 views

Feature selection when using cross validation

I have a limited size data set of 385 entries on which I want to run multiple classifiers and compare their performance using the WEKA experimenter. The number of attributes in this data set is large,...
3
votes
1answer
1k views

Minimum number of instances to create a decision tree

I'm kind of new doing data mining, so sorry if my question is not very clear. I'm working in a project that is aiming to do data mining over the interactions of the students with a e-learning ...
3
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0answers
550 views

Microarray data: suggestions on Feature selection + Model training scheme?

I have a microarray expression dataset (46 samples, thousands of attributes) and I want to perform feature selection first, and, based on this subset of features (shouldn't be more than 4 or 5, based ...
3
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0answers
1k views

Weka J48 decision tree problem

I have a CSV dataset which contains mean (Numeric), spread (Numeric), review (string), ...
3
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0answers
1k views

Combine MultiClassClassifier and MetaCost in WEKA and make cost matrices for each binary classifier

Ok, I have a classification problem in which i need to classify instances into one of 5 classes. The class distribution of the classes is imbalanced however. These are the frequencies of instances ...
2
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2answers
5k views

What is class correlation?

I am referring to iris.arff dataset that comes with Weka distribution. There are 3 classes and 4 attributes. It gives below information regarding the 4 attributes- ...
2
votes
1answer
227 views

Using the appropriate machine learning algorithm

I am not sure if this is the right forum to ask this. I have some data of the houses, like their size(in square meters), if they use aircondition, how many residents live in, I have their electricity ...
2
votes
2answers
3k views

Does Weka have an online API?

I am doing a project with Weka with clustering algorithms (simple k-means, expectation-maximization and OPTICS). I would love to be able to call those algorithms over the internet. So does Weka has ...
2
votes
3answers
1k views

Implementing the 0.632+ bootstrap method using the Weka Java API

I am trying to implement the 0.632+ bootstrap estimator (as proposed by Efron and Tibshirani 1997) in order to perform certain benchmarks and compare it with other cross-validation methods, such as ...
2
votes
1answer
12k views

Interpretation of a WEKA result buffer - confusion matrix and performance

I want to know how to get several performance measurements of a generated WEKA model. Note that I am predicting a two-class variable, Alive or ...
2
votes
2answers
786 views

Excluding false values with association rule mining in Weka

I am using Weka 3.6 to do Association Rule mining. In our data set, each transaction is a word, and each letter in the word is an item. The rules that we are mining would be in the format of ...
2
votes
2answers
7k views

Weighted average of precision (or recall) of all classes?

How to compute the global precision given the precision calculated for each class? Is it just the average over classes precisions? When I use Weka the global precision is not computed as the average ...
2
votes
2answers
258 views

Predictive Modeling question on Weka

I would like to predict the number of flu cases in the future using predictive modeling. I am very new to statistics, so I'm not sure which classifier to use in this case. For the attributes, I'm ...
2
votes
1answer
3k views

Why doesn't classifier accuracy increase linearly with k in k-fold validation?

I am experimenting with WEKA and I'm trying to understand the impact of k in cross-fold validation. It seems reasonable to me that the higher k is, the more accurate the classifier will be (with ...
2
votes
1answer
1k views

Is it wrong if I get training accuracy lower than test accuracy?

I have a dataset with 20000 instances in training, 2300 attributes. I did 10 fold CV and executed on a test set with 9000 instances with naive bayes and J48. The 10 fold CV accuracy is low compared to ...
2
votes
2answers
535 views

Learning a model which can fit the training data accurately

I am using weka for creating a model on a training set for a classification task. I am trying different classifiers for this. But when I try to give one of the data points which are present in the ...
2
votes
2answers
4k views

What are good criteria for performance evaluation of algorithms in a regression problem?

I'm classifying different algorithms on the wine quality dataset. The quality ranges from between 0 - 10 based on 11 other attributes. Here is the data. I'm treating this as a regression problem. ...
2
votes
1answer
1k views

J48 decision trees in weka

I am using J48 decision tree classifier in weka. In the testing option I am using percentage split as my preferred method. The split use is 70% train and 30% test. My understanding is that when I use ...
2
votes
3answers
2k views

Cross Validation with Preprocessing (Normalization, Discretization, Feature Selection)

I am now trying to evaluate my model with cross validation. My dataset contains some numeric and nominal attributes. Here, I carry out the following data preprocessing tasks: A. Normalization: Min-...
2
votes
1answer
386 views

Clustering related areas with k-means in WEKA

I am trying to cluster related areas of knowledge. A sample of my file is: ...
2
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2answers
1k views

Summary on correctly classfied instances WEKA for a 10-fold cross-validation

I ran a 10-fold cross-validation BayesNet (but it could be any method in WEKA), and the output I got was (among other things): ...
2
votes
1answer
10k views

How to find TP,TN, FP and FN values from 8x8 Confusion Matrix

I have confusion matrix as follow: a b c d e f g h <-- classified as 1086 7 1 0 2 4 0 0 | a 7 1064 8 6 0 2 2 0 | b 0 ...
2
votes
1answer
486 views

Binary classification of dated text documents with seasonality

I have a collection of training documents with publication dates, where each document is labeled as belonging (or not) to some topic T. I want to train a model that will predict for a new document (...
2
votes
0answers
652 views

How the Correlation Matrix is built for PCA in Weka?

Just to give a context, I want to use PCA (Principal Component Analysis) to identify which attributes are similar to others, so I can use just one (or a subset) of them. The correlation matrix of n ...
2
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0answers
52 views

Requirement on data distribution when using certain data mining classifiers

I am a little bit confused on whether data mining classifiers make any assumptions about the distribution of the data. I myself have a computer science background, but when I have discussions with an ...
2
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0answers
2k views

Outlier detection in time series data

I checked different questions on similar topics, but none were exactly the answer I wanted and I am confused. I am working with big data, the data has a bursty nature with high frequency. I ...
2
votes
0answers
2k views

Ripper algorithm on large data sets

I've got a supervised learning problem where I've got about 15 features, mostly numeric, and I'm mapping these to a set of 5-7classes. Using decision trees or forests, I'm able to get confusion ...
2
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0answers
837 views

Model selection in Weka through cross validation for regression problems

Does anyone know an approach to performing model selection in Weka through cross validation for regression problems? As far as I can tell, the cross validation is implemented in Weka just to assess ...