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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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+50

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
16 views

Using svm in (weka java) [on hold]

While using svm in java (weka) with nominal input set, does the inbuilt algorithm itself does the one-hot encoding or is it required by the user to do so?
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13 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
35 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
11 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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0answers
15 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
7 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
81 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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0answers
151 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
103 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
114 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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0answers
47 views

Why are Radial basis function networks not particularly suitable for extrapolation?

Assuming you have a regression problem where the test data is quite likely to be outside the range of the training data; hence, the model needs to extrapolate from the training set. Why are Radial ...
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1answer
38 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
25 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
254 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
124 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
76 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
379 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
281 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
133 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
325 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
92 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
284 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
60 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
53 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
322 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
257 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
654 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
633 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
281 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
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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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0answers
333 views

Cross validation in weka or scikit-learn [closed]

I'm trying to perform cross validation using weka and scikit-learn, but wasn't sure which to use based on my requirement below. If we are doing 5-fold cross validation in weka or scikit-learn, does ...
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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
126 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
339 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
156 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
58 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
161 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
334 views

What is the possible reason that my R squared value equal to 1

I have one natural data set of biological data from my lab such as binding energy, exon type and oligo length etc. And my goal is to train a model to predict skipping rate. I used weka with no filter ...
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2answers
1k views

Weka - random forrest always predicts the same class

I am classifying Portuguese tweets in to three classes, news, noise and relevant. I have used the weka gui to identify a classifying pipeline that gave good results. STWV -> Attribute Selection -> ...
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1answer
242 views

correlationAtrributeEval Weka [closed]

I am new In data mining and Weka. I am working on "Ta_Feng" data set and my Intention is to apply Pearosn's Correlation coefficient to calculate correlation between User and Item attribute in my case ...
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1answer
834 views

Weka PART algorithm output

I am using Weka PART on my data set, and it is providing the rules below: ...