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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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13 views

Interpret the clustering results of Weka to measure the performance [closed]

I'm having the Boston dataset, where it's class variable in the housing price. So I think regression is more suitable for this dataset, so we can predictions. I'm using Weka for this. I used several ...
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14 views

Binary classifier, class is a nominal variable, how many neurons in outer layer? [duplicate]

Please pardon if my question seems silly, but I am a self-learner and new to this. I tried finding information in Ian and Frank's book, and also online and in papers but I must be missing the point. ...
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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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0answers
79 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
37 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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1answer
14 views

Can we apply SMOTE on data with k-fold CV

The SMOTE for the imbalance should be applied for the training data only, right? Can we still do it (perform SMOTE on training data) while we select the k-fold CV and does not go for splitting the ...
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1answer
42 views

What does this ROC value mean?

What does this roc value mean? How do I interpret it? Are there values which help in inferring it like in case of kappa?
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2answers
122 views

How to binarize data for FP Growth in Weka?

I have a CSV file where all comlumns contains numerical values except for the quality column which contains nominal values. I want to use FP Growth Weka algorithm ...
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0answers
18 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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1answer
126 views

K-means calculate MSE in Weka

I am doing some clustering analysis with Weka and decided to apply the k-means algorithm (the clusterer SimpleKMeans). On my first analysis I ran the algorithm with 2 clusters. Then, after finding ...
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0answers
87 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 ...
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19 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
10 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 ...
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1answer
114 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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245 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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0answers
14 views

Meta-method in WEKA to apply forecasting for multiple sequences determined by a partitioning variable

Is there a way to implement multiple forecasting models in WEKA, where instead of one sequence of events there are multiple sequences, for different (user) identifiers? Let's say, a traditional ...
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1answer
150 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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0answers
129 views

What is the meaning of AUC being high when accuracy is not? [duplicate]

I'm testing several classifiers in Weka Experimenter. Some of them have — at the same time — low accuracy (Percent_correct statistic) and high AUC. How should the quality of such ...
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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 ...
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1answer
32 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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2answers
325 views

WEKA Visualization: getting class percentages

I've just started out trying on ML. In WEKA, when I try to visualize a data set I find it hard to tell the class ratio for a certain nominal attribute value due to the differing amount of instances, ...
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0answers
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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1answer
94 views

Standardize a sample dataset

I created a model with J48. Before creating the model, data were standardized. Now I want to test this model with a sample dataset. Before applying data to the model, I believe data should be ...
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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 ...
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0answers
445 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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2answers
328 views

How to tweak a Weka model? [closed]

I know how to run a Weka model, but I'd like to tune some parameters. How do I do that? Thanks, a newb
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0answers
169 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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1answer
374 views

Log-Likelihood in EM Cluster

I am doing clustering in Weka for a school project. I am trying to compare two Weka outputs with log-likelihood: Number of clusters selected by cross validation: 6 ...
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2answers
2k views

Cross-validation with unbalanced-classes

I'm a little confused on how to manage my data set with WEKA.(for data mining) I have a Dat set including 11377 record classified as follows: 11111 records have class YES 266 records have class NO ...
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1answer
180 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 ...
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1answer
317 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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1answer
65 views

Weka - only care about “top” instances

I'm trying to classify instances between 2 classes ("good" and "bad"). My ultimate goal is to be able to predict good instances, but I don't need to identify all good instances. For example, say I ...
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1answer
38 views

I need to see the incidences in my data set in WEKA

I have a dataset that contains 44804 instances, each with the attributes: diagnoses, age and quantities (same diagnoses includes). I want to see which diagnosis is most seen for a given age. For ...
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1answer
60 views

Is value of correlation matrix enough criteria to delete an attibute?

I need to do some clustering with my data set. I have 200 attributes and 18 tuples only. So I am trying to do some data cleaning. I deleted all attributes that has 0 as data and reached till 165. Now ...
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1answer
1k views

guide for text classification using weka

I have a set of 2000 small texts (each less than 500 words) that I manually categorized. All the texts are in the same main subject, and I want to separate them into distinct groups based on their ...
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1answer
379 views

MultiBoost vs Gradient Boosted Decision Trees

Why isn't there an implementation of GBDT in Weka? (Java ML library) Instead the recommendation is to use the MultiBoost algorithm with J48 (Java implementation of Decision Trees - C4.5 algorithm). ...
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0answers
278 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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2answers
796 views

Weka clustering methods greyed out

I generated a csv file with 167 attributes and around 5000 entries. One is a nominal attribute, two are dates and the rest is numerical. I can import the file into the weka explorer without problems. ...
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0answers
687 views

How does a decision tree split on a categorical variable? [duplicate]

Some implementations of decision trees (eg cran/tree) can split on categorical variables where the split separates the variable into 2 groups: ...
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0answers
317 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 ...
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0answers
64 views

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

Classifier Model Linear Regression Model bug = ...
2
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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 ...
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1answer
1k views

How do weka classifiers deal with missing values? [closed]

I tried using a training set that has missing values. I applied filters (like replace missing data) and then after there were no more missing data I applied naive bayes, trees etc... I thought this ...
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1answer
2k views

Classification and mixed categorical and numeric variables

I've been working a little with weka and so far I haven't made my own database to apply a classifier but I've tried to look at the already existing files and from what I've seen there is absolutely no ...
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1answer
2k views

Symmetrical uncertainty and Correlation based feature selection

I'm try to study the correlation-based feature selection (cfs) form http://www.cs.waikato.ac.nz/~mhall/thesis.pdf but I'm not sure the relation between cfs and Symmetrical uncertainty (SU) theory, If ...
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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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0answers
353 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
193 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
165 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 ...