0
votes
0answers
26 views

Classification using correlation

Given two correlation matrix (each $p \times p$), where each belongs to a different group, is it possible to classify a new sample into one of the group (based on the correlation matrix only)? What ...
0
votes
0answers
16 views

different feature types for classification

There has a data set with several features. One feature is of the type of continuous numerical values; another feature is of the type of categorical values, such as A, B and C. If I want to build a ...
0
votes
2answers
125 views

When to avoid Random Forest?

Random forests are well known to perform fairly well on a variety of tasks and have been referred to as the leatherman of learning methods. Are there any types of problems or specific conditions in ...
1
vote
1answer
19 views

How should the precision/recall be calculated for classes in datasets with NO true class instances?

I have built a classification model to recognise a class and I have evaluated it on several datasets. The problem is that some of these datasets do not have any true instance of the class in question, ...
0
votes
0answers
3 views

what is the meaning of the Samples in NER?

I would like to know in NER (Named Entity Recognition ) problem , which concept should be considered as samples? each token as a sample? or each sentence ? or each Named Entity should be considered ...
2
votes
0answers
38 views

Unbalanced dataset - ROC curve to compare classifiers?

I use the machine learning software WEKA for data mining on biological data. I would describe my dataset as unbalanced: It comprises around 2000 instances, ...
2
votes
2answers
86 views

Reproduce linear discriminant analysis projection plot

I'm struggling with projection points in linear discriminant analysis (LDA). Many books on multivariate statistical methods illustrate the idea of the LDA with the figure below. The problem ...
1
vote
0answers
11 views

Learned production test

To validate the acoustic performance of a product, we are using hand-engineered features and thresholds. Everytime a new hardware problem arises we have to at least tweak a parameter and at worst add ...
0
votes
0answers
20 views

semisupervised classification training on all or part of unlabeled data

I have 3 sets of data. A positively labeled dataset. An unlabeled dataset that has for sure positive (around 75%) and negative data. An unlabeled dataset that has for sure positive data and maybe ...
0
votes
0answers
16 views

Extraction of a decision boundary (LDA) after a systematic querying of the feature space and convolution with Sobel filter (examples in numpy)

I am doing some experiments with LDA (Linear Discriminant Analysis), in python. Now I am at the point in which I would like to display the separation planes in the 3-dimensional feature space. I ...
0
votes
0answers
6 views

Categorizing text into IPTC subjects

Does anyone know where I can find a corpus I can use to train a classifier into IPTC news categories (http://www.iptc.org/site/NewsCodes/) ? A google search was not very useful. Thank you
0
votes
0answers
34 views

Algorithm for online handwriting recognition

Is there any specific algorithm for online handwriting recognition? The algorithm should recognize non-cursive and cursive handwriting. I know there is already a similar post on stackoverflow.com, ...
1
vote
0answers
15 views

Abnormalities in results L-LDA

For my research I am using Labelled Latent Dirichlet Allocation (L-LDA) on Reuters-21578 ModApte split dataset. In this dataset the news stories have a title and a body. To test the effect of L-LDA, I ...
0
votes
1answer
18 views

How to apply properly k-nn algorithm when having several attributes

Let assume I have a dataset like this dataset where there are several textual attributes even continuos attributes like age. I have always encountered cases where k-nn is applied on just two ...
2
votes
1answer
36 views

One-class Classification of multidimensional vectors

I have a m x k User-feature matrix (m >> k) obtained by factorizing an original User-websites matrix (m x n) that has #page views as entries. Additionally, there are users (say r) who have been ...
2
votes
1answer
56 views

For a model like this what performance measures can I calculate and how?

Methods: From the machine learning literature, I understand different parameters can show performance of model in machine learning. I would briefly expand my understanding with confusion matrix: ...
1
vote
2answers
133 views

High precision with low recall SVM

I'm classifying a data set using SVM and those are the precision and recall values for two classes. ...
1
vote
1answer
32 views

SVM Classification with Duplicate Training Instances

I'm using SVMs with linear kernel for sentence classification (binary). My dataset contains many duplicate instances i.e. many sentences in the training set have identical feature vectors. In the ...
1
vote
1answer
60 views

Simple SVM Question

For a linear SVM, the documentation tells me the formula is: $$ \frac{1}{2}w^Tw+C\sum\limits_{i=1}^l\xi_i$$ Please explain to me in layman's terms what w (and ξ) represent. Is w the distance to the ...
0
votes
0answers
21 views

Softmax regression or $K$ binary logistic regression

For a multi-class classification problem, we can use $K$ binary logistic classifiers, or one softmax regression classifier, so how to make the choice between the two? IMHO, the $K$ binary logistic ...
3
votes
3answers
56 views

Recognition of simple patterns and prediction

I have been doing supervised learning and classification with multilayer perceptron for some time. But now I need to use unsupervised learning to infer the presence of a pattern and I would need some ...
2
votes
1answer
86 views

What is the difference between a multi-label and a multi-class classification?

What is the difference between multi-label classification and multiclass classfication. Speficially, what is the difference between a label and a class? Please provide a clear example. "Multiclass ...
1
vote
0answers
25 views

Binary classification of dated text documents with seasonality

I have a collection of training documents with publication dates, where each document is labeled as belonging (or not) to some topic T. I want to train a model that will predict for a new document ...
0
votes
0answers
30 views

What is the simplest way to classify airplan manuvers?

Suppose we have declared four motion types for air-plane. If we represent each maneuver with a trajectory line, what is the best classification method to retrieve the trajectory pattern with a similar ...
4
votes
1answer
102 views

Is KNN a discriminative learning algorithm?

It seems that KNN is a discriminative learning algorithm but I can't seem to find any online sources confirming this. Is KNN a discriminative learning algorithm?
0
votes
1answer
39 views

SVM cost parameter

In a SVM with linear kernel, could you explain to me what exactly the C parameter is/represents? An example why it's important to select a good value for C would also be appreciated. Thank you.
1
vote
1answer
76 views

Maximum Entropy Model for classification, what to use as context & feature?

I'm building a Maximum Entropy Model to classify some text, based on paper "A Maximum Entropy Approach to Natural Language Processing" by Berger et.al. It's similar to POS tagging. Below is some ...
0
votes
0answers
42 views

Training and testing on Unbalanced Data Set

I used SMOTE algorithm in R for class balancing. My data size has 13000 rows, I had 7% minority class in my sample now I used SMOTE( Synthetic Minority Oversampling Technique) for class balancing such ...
0
votes
1answer
27 views

how to handle (many) false positives in training dataset for logistic regression classifier

I want to train a logistic regression dataset. I have a quite big training data set ( >100 000) and have around 10 features I can train on. Half of my training data is negative training data and I ...
3
votes
1answer
43 views

What is the difference between a “learner” and “classifier” in supervised learning?

This question stems from Pedro Domingos' excellent paper "A Few Useful Things to Know About Machine Learning." The paper is extremely clear and well-written, but I still have a clarification question. ...
0
votes
1answer
47 views

Way to train Hidden Markov Model in R with multiple sequences

i have multiple sequences for each of two states. I'd like to train a HMM with these to predict the state for unkown sequences. Here is an example for this problem: ...
0
votes
0answers
48 views

What algorithms should I use to perform job classification based on resume data?

Note that I am doing everything in R. The problem goes as follow: Basically, I have a list of resumes (CVs). Some candidates will have work experience before and some don't. The goal here is to: ...
0
votes
1answer
58 views

How do I detect state change in multivariate time series?

I have a multivariate time series . For each row in the data we have the values of inputs and a label for stability (0 or 1 ) . What are the algorithms that can detect the stability for an unlabelled ...
0
votes
2answers
59 views

Best feature selection method for naive Bayes classification

i want to make classification with naive Bayes. I have got about 100 Features. Numerical ones as well as categorical ones. Since i want only the most relevant ones to be included for the ...
0
votes
0answers
16 views

Correlation between sensors

Background: A home wired with multiple sensors, measuring attributes like temperature, light, motion etc. In addition, a multitude of actuators that can carry out an action like opening a door, ...
0
votes
0answers
9 views

Regularization in multinomial manifold (k-simplex) space

I have a multi-class classification problem. In order to reduce the feature space, I have mapped my weights ($w$) to a multinomial manifold (or k-simplex) and compute the new weights ($v$) as follows: ...
2
votes
3answers
150 views

Naive Bayes: Imbalanced Dataset in Real-time Scenario

I am using scikit-learn Multinomial Naive Bayes classifier for binary text classification (classifier tells me whether the document belongs to the category X or not). I use a balanced dataset to train ...
1
vote
0answers
25 views

Open, multi-class , active learning classfiers

I am trying to classify text documents using a huge corpora. Thats a huge tagset (more than 1000 tags). Corpus will have 1000 samples for each tag. But the tagset is not closed. New tags can be added ...
0
votes
0answers
18 views

Classification More Robust Than Regression

Are neural networks using classification more robust / reliable than using regression to produce a single value? The only reason I would think so is that it would be easier for the network to adjust ...
0
votes
1answer
14 views

Solving feature bias issues in Learning to Rank with implicit feedback

I have a learning to rank system where implicit feedback (from user clicks) is used to determine +ve and -ve examples for the training. The problem is that (obviously) the learner sees only the top ...
1
vote
1answer
50 views

Reverse AUC interpretation

Given a classifier (SVM) classifying in 2 'classes' (+1 or -1) for prediction purposes. It has an AUC score of 0.28, meaning its success rate is lower than just random predictions. If I just do the ...
1
vote
0answers
65 views

What should I use - Multi label classification or Multi class classification?

In my dataset, I have 2 labels, positive and negative. Most samples belong to only one class, either positive or negative. A small fraction of samples take both labels i.e. both positive and negative. ...
0
votes
0answers
30 views

BOW prediction of cluster for training data

I am creating a bag of visual words for classification of videos. I am not using SURF descriptors and that is why I couldn't use OpenCV's BOWImgDescriptorExtractor ...
2
votes
2answers
56 views

Cluster Data based on Distribution

I have a list of diseases for my research. For each disease, I have a list of ages for the diseases. "Breast Carcinoma" may be a list of [1,2,2,3,4,5,5,5,5,5] while "Adrenal Cortex Neoplasms" maybe be ...
1
vote
0answers
17 views

How to combine n confusion matrices

Suppose you have $n$ confusion matrices, each from a different independent classification on a dataset. Suppose each classification is ran on a proper subset of the dataset, and usually these subsets ...
0
votes
0answers
25 views

Supervised classification on different time series

I have 300 files, each file has a time series data with a class label(0 or1) for each data point.I want to build a classifier, which can predict the class of a new time series data. How should I ...
2
votes
0answers
47 views

How to calculate accuracy of each feature

I read some paper (* about predicting user retention in StumbledUpon) and saw the authors provide a list of features with accuracy of each feature with the following explanation: As decision ...
0
votes
1answer
36 views

How is the training set constructed for multi-class SVMs?

Support vector machines do binary classification. If there is more than two classes, it is possible to train several classifiers instead of one. Two common approaches are training one vs. one (each ...
0
votes
0answers
21 views

What's the safest way to resample to ensure equal class frequencies in training data?

I am working on a number of EEG data sets for binary classification. A good example of one is publicly available here. If you look at what Matthias Kaper did to classify that set, one thing that ...
0
votes
0answers
49 views

R choosing the right classification approach for $ transaction volume categories

Our customers are Merchants and use our online payment service. Before they started using our service, they indicated how much $ transaction volume they will make per year. However this turned out to ...