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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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1answer
128 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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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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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 ...
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1answer
156 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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1answer
16 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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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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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 ...
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1answer
201 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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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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0answers
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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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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0answers
84 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
102 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
168 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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1answer
15 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 ...
1
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1answer
487 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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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
158 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
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
1
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1answer
171 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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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-...
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0answers
96 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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2answers
2k views

Latent Dirichlet Allocation as input for WEKA

I am using the Weka API for my research about document classification. I wish to apply Latent Dirichelet Allocation on my dataset followed by using a classifier in Weka. However, it is not so clear to ...
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0answers
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 ...
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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 ...
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1answer
2k 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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0answers
262 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
738 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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3answers
554 views

Normalization in SVM

I have applied libsvm with a linear kernel to a set of instances and I have obtained a 68 % success: ...
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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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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 ...
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
286 views

Implementing an Adaboost Classifier

I have generated an adaboost classifier in Weka on a dataset where each instance falls into one of two classes. The result was a number of decision trees, each assigned a weight. What is the ...
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0answers
131 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 ...
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
95 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 ...
1
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2answers
336 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. ...
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 ...
1
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0answers
457 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 ...
0
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1answer
4k views

10 fold cross validation model in weka

I'm trying to build a specific neural network architecture and testing it using 10 fold cross validation of a dataset. Now building the model is a tedious job and Weka expects me to make it 10 times ...
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4answers
3k views

Can C4.5 handle continuous attributes?

I'm trying to play with the breast cancer data available through UCI: https://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/wdbc.data When trying to classify the data ...
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3answers
1k views

Expectation Maximization-Log Likehood interpretation

I am using EM algorithm in weka for genomic data, get the results in the images, but a don't know how interpret the log likehood index. Is better when is higher or lower, negative or positive. How ...
1
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0answers
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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2answers
332 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
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 ...
1
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0answers
171 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 ...
0
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1answer
388 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 ...
1
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1answer
528 views

Manipulating the number of neurons in the hidden layer in Weka [closed]

I'm classifying datasets in Weka with a MLP. My question is how can I change the number of hidden neurons in the hidden layer? Only the option about number of hidden layers is available.