Questions tagged [weka]
Weka (Waikato Environment for Knowledge Analysis) is a collection of machine learning algorithms for data mining tasks.
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How calculate computational complexity (BigO) of ML techniques using Weka?
I'm trying to get the bigO notation from these algorithms: Alternating Model Tree, SMOreg, LSTM, Multilayer Perceptron, LeastMedSq, and M5Rules.
Since BigO notations are represented as following
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2answers
43 views
Numeric variable with outliers as a categories
I'm working with a dataset that has a few variables that I'm having difficulty trying to preprocess. So one of them is called MENTHLTH where it is a numeric variable.
The point of the variable is to ...
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0answers
58 views
Difference between One Rule Classifier and Decision Stump in WEKA
WEKA Explorer seems to come up with two different models for OneR (rules) and Decision stump (trees). Is has to be the underlying measure of "best split" that is different. But for a single ...
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0answers
20 views
Cross-validation giving better results than separate test test
I am using J48 in Weka.
The accuracy results of the cross-validation is about 99.9% but when I provide a separate test set the accuracy drops to about 65% or less.
So the question is why there is a ...
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0answers
25 views
Calculating three average precisions and a single value for ROC from raw predicted class outputs
I'm not a statistician or mathematician so I apologize if I use any terms incorrectly. Please do point out any errors in my use of terminology.
The four values I need are the equivalent of Weka's ROC ...
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1answer
469 views
Calculating Specificity from Weka output
In short I need to know or calculate the sensitivity and specificity from Weka 3.8.4 output.
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1answer
443 views
Leave-One-Out CrossValidation with Weka
I have a dataset consisting of 5 subjects (5 different virus names and 5 benign program names). The programs belong to the class "benign" and the viruses to the class "infected". There are 1000 ...
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1answer
259 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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0answers
220 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
1k 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 ...
1
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1answer
82 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
54 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
649 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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1answer
981 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
336 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
321 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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492 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
261 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 ...
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229 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
45 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
37 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
507 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
184 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
116 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
2k 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
645 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
448 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
244 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
587 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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3answers
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
525 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
407 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
92 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
40 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
95 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
2k 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
570 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
314 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
1k 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
781 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
405 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
111 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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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 ...
0
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1answer
3k 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
3k 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
198 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 ...
2
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0answers
371 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
212 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
72 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 ...
