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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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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 ...
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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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0answers
653 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
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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 ...
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87 views

How to create a test set in stacking when doing cross validation

I am using Weka to implement stacking with k-fold cross validation. As I understand, we first divide our dataset in to k folds, then we use k-1 folds for training and 1 fold for testing. This ...
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0answers
110 views

Cross validation or percentage split

I got a data-set with 50 different classes. Around 40000 instances and 48 features(attributes), features are statistical values. I am using weka tool to train and test a model that can perform ...
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0answers
98 views

Meaning of confidence factor in J48

I try to use J48 classifier from RWeka library in R (C4.5 algorithm). I can parametrize this classifier with C parameter which means 'confidence factor'. What does this value exactly mean? I know that ...
1
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1answer
157 views

TF-IDF String to Vector Weka bias

For example, let's say I have a text dataset like: "words text etc",label "words text etc",label "words text etc",label If I use Weka's String to Word ...
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141 views

What is a good percentage value for SMOTE in Weka

I am using the oversampling technique named as SMOTE to balance my dataset in Weka. To balance my dataset I needed to use 1300 as my -p (percentage) value. The default -p (percentage) value is 100. ...
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459 views

Interpreting results from WEKA

I am trying my to built a model that predicts whether or not customers will churn, using a dataset with 7000 instances (rows) and 20 features. I am using WEKA and experimenting with a J48 Decision ...
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172 views

Should classes be balanced before or after splitting into sets?

I've split my data and performed pre-processing. I ran some basic classifiers on it and got accuracies within 70-80%, which to me seems fairly low. One thing I didn't do was balance my classes before ...
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67 views

How to predict the error accuracy using these values from weka and how to intepret the output?

Classifier Model Linear Regression Model bug = ...
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0answers
140 views

Is there any rule of thumb when choosing a feature selection method

In a prediction experiment with regularized regression methods (Ridge, Lasso, and Elastic Net), I have tried two feature-selection methods prior to running regression, and I have obtained very similar ...
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356 views

Selecting features highly correlated with target while preserving low inter-correlation

I wonder if sklearn has any feature selection mechanism that chooses features that are highly correlated with target variable and maintains low inter-correlation ...
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0answers
197 views

ML Datasets for Telecommunications Networking

I am working on a telecommunications networking project and I am interested in datasets which contains the following features: source/destination IP packet size. protocol. Port number. I have been ...
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0answers
63 views

400 features and 100 classes using weka

I am working on a classification problem, where I have 400 features(all are numeric), and 100 classes and I have 26,000 examples for training. In my project I am using Weka and I have tried different ...
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0answers
166 views

Weka random forest classifier

I have one problem with choosing a classifier and I will really appreciate if someone could help me with that. I have to use weka J48 decision tree classifier, but I can't find a package in python to ...
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0answers
94 views

Why random forest performs better when converting categorical attributes to numerical ones?

I have a dataset with 15 attributes, 6 are numerical and 9 are categorical. Among the categorical ones, some have about 3 levels, some about 10 levels and 2 of them about 500 levels. I'm training a ...
1
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0answers
739 views

Leave- one- subject-out cross validation

I am doing KNN classfication on a dataset composed of 1040 instances. I have 40 subejcts each having 26 samples. I want to do a LOSO validation in WEKA. I divided my data in a way that each time a ...
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244 views

What is the difference between weka CostSensitiveClassifier and weka MetaCost?

I have read that weka MetaCost's implementation refer to the implementation explained in Pedro Domingo's paper (1999). But I didn't find any explanation of weka CostSensitiveClassifier implementation. ...
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82 views

Per-instance cost-aware learning?

I have a situation where the misclassification cost depends on the instance, i.e. on the independent variables. In my training set I have for each instance the independent variables plus a vector of ...
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0answers
120 views

Obtaining exact output values of SMO based classification, before clearly demarcating them into classes

While running the SMO classifier in weka, if I have inputted my training labels as 0 and 5, (A binary set), then while running the classifier model on test data, are the outputs some decimal values ...
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375 views

ensemble methods:voting with average of probabilities in weka

output attribute is risky patient. Values are yes and no.if yes then patient is risky and if no then patient is not risky. If I am combining 3 classifier for classification model in weka, and if ...
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232 views

How to combine random forest from various trained models.

I am currently working on a training data set which is time dependent. I have divided the dataset into different time zones. For each month, I am training the model with training dataset and class ...
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863 views

How to address Boosting and Bagging decreasing the classification accuracy

For my classification, I use several algorithms available in WEKA, but with limited number of features. I got some accuracy levels with the algorithms I used and I tried improving the accuracies using ...
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0answers
845 views

Weka LibSVM one class classifier always predicts one class

I'm trying to use LibSVM classifier in Weka to build a one class SVM classifier. My training file has list of noun words. My test file has many words. My aim is to use the classifier to predict the ...
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0answers
1k views

J48 Handling Missing Value with Tree based Imputation

Aloha, currently i have some trouble and question zu implement some kind of special missing value handling in WEKA J48 algorithm using WEKA JAVA API. I want to test the performance of SHAPIRO ...
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346 views

What does Class Complexity mean in Weka?

When running Weka on my dataset, in the results printout I get the following rows: ...
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0answers
1k views

Evaluation of LMT (Logistic Model Tree) classifier results

I have been using the LMT Logistic Model Trees algorithm in some classification experiments. However, after reading the reference/documentation regarding the algorithm (Niels Landwehr, Mark Hall, ...
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0answers
3k views

How to combine WEKA classifiers

I need to utilize two different classifier to get best classification results. Since, it seems that they complement each other (not sure I am not expert btw). ROC characteristics are given below (...
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174 views

What should I do to compare different sets of data?

I am a beginner in statistics, and I want to learn machine learning :). Therefore, I have gathered some sample data to practice. But, the problem is I want to create a feature (or attribute), which is ...
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0answers
8 views

Is there a way to assess how much and in which direction a predictor is associated with class in my classifier?

I searched the forum, and couldn't find a matching question. I am building an MLP to predict an outcome (occurrence of a medical condition) in Weka. Previously I identified positive and negative ...
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19 views

How to understand 2X2 confusion matrix one-r?

with this data set when applying one-r with weka choose age group: but I do not understand how weka made this confusion matrix
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21 views

Why does Weka output decision tree with multiple children nodes of the same target variable?

I'm working with this dataset. I broke the quality class into 3 categories: low, medium and <...
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0answers
11 views

Hierarchical clustering based on relative error

How can I use Weka to do hierarchical clustering, but based on the % difference between two elements rather than absolute elements? Let's say I want to draw many circles with specific radii. I have a ...
0
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1answer
129 views

SVM and correlation

Can anyone guide me about the feature selection based on correlation using SVM? RBF kernel check the correlation too or not? I am using weka and matlab. Any help would be appreciated.
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263 views

How to deal with a negative Kappa in classification?

I have a dataset with one binary class to be predicted, with 18 binary predictors and 17400 rows. Here I used a stratified split, with approximately 85% (14648 rows) for training and 15% (2752) for ...
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1answer
41 views

SVM decision non linear

As I understand, to perform a decision in a non linear case (using a kernel) I use the following: $f(x) = sgn(\sum_{i=1}^{n} y_{i} \alpha_{i} \boldsymbol{k}(x,x_{i})+b)$ Where i=1,..n are the ...
0
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1answer
35 views

Performance measures in Predictive models

I developed predictive models and I reported G-mean ,F-measure, Sensitivity, and Specificity which are very low. i wonder if anyone has a reference for the threshold of these measures ? I want to ...
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1answer
208 views

Negative feature value

I use a logistic regression model for reranking some documents where a normalized features of some candidates may have negative real value so that its predicted value may get lower score(low ...
0
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1answer
322 views

How to interpret coefficients of nominal independent variables in Weka?

I'm struggling a bit with interpreting the output of a linear regression in Weka. This is my model: ...
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0answers
283 views

Decision tree: Perfect classification with (a dicotomic) class noise at 100%, but almost null prediction with noise at 99%. (Tried 2 alg in R). Why?

I am using a dataset with a dicotomic class and testing how noise affects the decision tree j48 - from Rweka, using R - performance. I´m adding noise, and using confindence factors from 0.01 to 0.5 ...
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0answers
326 views

Goodness-of-fit vs maximum likelihood for logistic regression?

From what I understand, maximum likelihood is used to estimate a parameter alpha in a way that maximizes the probability P(Y=|x,alpha) for example. It is used for logistic regression in order to get ...
0
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1answer
170 views

ranking neural net models with feature selection

I have a sample with around 2000 observations and 10 variables which im using for classification. I plan on classifying the data with a neural net, but before doing so im using Weka's attribute ...
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0answers
113 views

Are Logistic Model Trees robust to imbalanced datasets?

I am trying out Logistic Model Trees (Weka implementation) with very imbalanced datasets. Is anyone aware of their robustness without the need of preprocessing steps (such as SMOTE)? My preliminary ...
0
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0answers
738 views

Accuracy decreased after feature selection

For my machine learning study, I tested different algorithms like SVM, SMO, Naive Bayes, Trees etc. All the algorithms resulted with low accuracy levels. In fact the highest accuracy I obtained was 46%...