Hi, I have problem with my model in weka (j48 cross-validation) that many instances are classified wrong when it comes to the second class. Is there any way to improve it or rather not? I'm not an expert in weka. Thank you in advance. My output is above. In NaiveBayes it presents better but still TP Rate < 0.5 for the second class. NaiveByes weka
1
There are 1 best solutions below
Related Questions in WEKA
- I keep getting a "NoClassDefFound" error with Weka Ai using Java. I keep getting this Error?
- How to treat integer attributes in WEKA i.e. number of bedrooms (cannot be float values)
- Dataset not being accepted by Weka's J48 plugin (C 4.5 algorithm)
- weka inital heap size memory allocated
- Problem with Decision Tree Visualization in Weka: sorry there is no instances data for this node
- How can I limit the depth of a decision tree using C4.5 in Weka?
- Weka supplied test set didn't process the full dataset
- converting a csv file to arff file using weka converter, but it is not counting enough columns
- i have loaded a csv file in weka tool but J48 is not highlight
- Why am I getting these exceptions when trying to load a .csv file into Weka 3.8.6?
- converting a csv file to arff file using weka converter
- WEKA EEG data Filter creation
- How can I see the ideal range of a numerical independent variable according to its dependent variable?
- Intepreting WEKA data
- Java Weka API: Getting ROC Area values
Related Questions in NAIVEBAYES
- Normal Bayes Classification
- sklearn ComplementNB: only class 0 predictions for perfectly seperable data
- How I get precision, recall, and f1-score from nltk.naivebayesclassifier?
- Content-Based Filtering for Tagged Posts
- Impossible to solve Feature name error while converting an XGBClassifier model to ONNX
- ValueError: operands could not be broadcast together with shapes (1,13) (14,) when classifying points with Gaussian Bayes and Gaussian Naive Bayes
- removing unseen labels in testing set
- How to properly prepare text data for processing it by already trained Naive Bayes multinomial model?
- Negative values in data passed to MultinomialNB when vectorize using Word2Vec
- NaiveBayes.active_trail_nodes() got an unexpected keyword argument 'variables'
- Using Naive Bayes for image classification in Matlab
- Naive-Bayes Probabiities: too many indices for array: array is 1-dimensional, but 2 were indexed
- the parameter 'token_pattern' will not be used since 'tokenizer' is not none'
- Mistaken result after one apply One Hot Encoder to test and train datasets
- Gaussian Naive Bayes gives weird results
Related Questions in J48
- Dataset not being accepted by Weka's J48 plugin (C 4.5 algorithm)
- i have loaded a csv file in weka tool but J48 is not highlight
- Weka j48 output
- How to install ant package in java correctly?
- Using WEKA Filters in Java - Oversampling and Undersampling
- make_Weka_classifier("weka/classifiers/bayes/naiveBayes") and J48 not working on my R?
- Zero-R model calculation of Sensitivity and Specificity using Confusion Matrix and Statistics with Caret
- Weka 3.8 - the decision tree J48 seem to have correct tree to predicate data but fail on the testing
- J48 Analysis With WEKA
- How visualize j48 tree in weka
- J48 algorithm in weka algorithm or flowchart steps
- What does Number of leaves and Size of tree mean in Weka?
- Weka - How can I improve J48 performance?
- How to get classification values in RWeka?
- What is the meaning of leaf node of J48 tree classifier
Trending Questions
- UIImageView Frame Doesn't Reflect Constraints
- Is it possible to use adb commands to click on a view by finding its ID?
- How to create a new web character symbol recognizable by html/javascript?
- Why isn't my CSS3 animation smooth in Google Chrome (but very smooth on other browsers)?
- Heap Gives Page Fault
- Connect ffmpeg to Visual Studio 2008
- Both Object- and ValueAnimator jumps when Duration is set above API LvL 24
- How to avoid default initialization of objects in std::vector?
- second argument of the command line arguments in a format other than char** argv or char* argv[]
- How to improve efficiency of algorithm which generates next lexicographic permutation?
- Navigating to the another actvity app getting crash in android
- How to read the particular message format in android and store in sqlite database?
- Resetting inventory status after order is cancelled
- Efficiently compute powers of X in SSE/AVX
- Insert into an external database using ajax and php : POST 500 (Internal Server Error)
Popular # Hahtags
Popular Questions
- How do I undo the most recent local commits in Git?
- How can I remove a specific item from an array in JavaScript?
- How do I delete a Git branch locally and remotely?
- Find all files containing a specific text (string) on Linux?
- How do I revert a Git repository to a previous commit?
- How do I create an HTML button that acts like a link?
- How do I check out a remote Git branch?
- How do I force "git pull" to overwrite local files?
- How do I list all files of a directory?
- How to check whether a string contains a substring in JavaScript?
- How do I redirect to another webpage?
- How can I iterate over rows in a Pandas DataFrame?
- How do I convert a String to an int in Java?
- Does Python have a string 'contains' substring method?
- How do I check if a string contains a specific word?
It is hard to reproduce your example with the given information. However the solution is probably to turn your classifiert into a cost sensitive classifier https://weka.wikispaces.com/CostSensitiveClassifier?responseToken=019a566fb2ce3b016b9c8c791c92e8e35
What it does it assigns a higher value to misclassifications of a certain class. In your case this would be the "True" class.
You can also simulate such an algorithm by oversampling your positive examples. This is, if you have
npositive examples you samplek*npositive example, while you keep your negative examples as they are. You could also simply double positive examples.