0
votes
1answer
23 views

Classification Accuracy

I am classifying text based on news headlines and I am achieving accuracy up to approx 80%. I want to improve it more. But issue is that when I calculate the same with synonyms using the code below: ...
0
votes
1answer
21 views

Decision boundary equation of the perceptron

As I know the standard linear equation has the following form in $R^2$: $w_1 x_1 + w_2 x_2 = b$ where $b$ is the intercept with $x_2$ Also I know that a decision boundary in $R^2$ for a perceptron ...
0
votes
0answers
6 views

How to validate classifier (built by using MLN method)?

I have developed a method (let's call it Method X) that has a classifier function. The classifier function was built by using MLN (Markov logic network). I need to ...
1
vote
1answer
35 views

Does using a kernel function make the data linearly separable?

I'm reading about SVM and I learned that we use a kernel function so the data become linearly separable in the high dimensional (vector?) space. But then I also learned that they use the soft-margin ...
2
votes
1answer
38 views

Gradient decay in neural networks

I read that in traditional feed-forward neural nets the gradients in the early layers decay very quickly and that this is 'a bad thing'. But I don't understand why. Can someone please explain what ...
0
votes
2answers
22 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 ...
1
vote
0answers
30 views

Rough estimates for training time of deep belief networks

I'm still learning about deep learning. However I'm currently interested to know if deep learning architectures scale well or not. Suppose I have a dataset with 1 million training examples, can you ...
0
votes
0answers
10 views

Why feature maps are indexed by two indices?

I'm reading about convolutional neural networks. As I understood a feature map is a set of neurons (i.e like a single hidden layer in traditional ANN). So why feature maps are indexed by (i,j)? ...
1
vote
0answers
35 views

A new piece of clue for document classification?

I am working on a document classification problem. I am using the typical vector space model to represent a document as doc-term vector. If document has some term, the vector entry for that term is ...
1
vote
1answer
30 views

How to implement a hold-out validation in R

Let's say I'm using the Sonar data and I'd like to make a hold-out validation in R. I partitioned the data using the createFolds ...
0
votes
0answers
20 views

Fisher's Exact Test to assess the significance of a difference between false positive rates

I have trained two binary classification models on the same data and evaluated them using the same test set. For each model I have calculated a false positive rate (and a count of false positives) at ...
0
votes
1answer
22 views

ML for specific classification problem

I have a training dataset for classification problem $X \rightarrow y$. Where $X$ is an $n$th dimensional real vector, $y$ is an integer number in $\{0, 1\}$. I want to solve the next problem: ...
1
vote
1answer
34 views

Why features compression is good?

I'm reading about deep learning and that in principles it's a features compression technique and that is why it works. Now my question is why compressing features from 200 or so into 4 is better? How ...
0
votes
2answers
43 views

Ensemble of models with different feature spaces

BACKGROUND I have data in which the dependent variable is binary with a highly-skewed distribution: <1% records are 1 (doers), >99% records are 0 (non-doers). I'm using logistic regression to ...
2
votes
0answers
24 views

Handwriting Recognition - Percentage Match

I'm currently working on a senior project and we've chosen handwriting recognition. Initially I thought that using machine learning algorithms were a good idea for this, but after the thought below ...
0
votes
1answer
20 views

how to compute minimum required vc dimension for a classifer to classify a specific data

Suppose we're given an N dimensional data to classify. To cope with this task we may choose a classifier that suits our desires more. However obviously not every classifier is capable of classifying ...
0
votes
0answers
31 views

HIstogram of oriented gradients (HOG) features descriptor theoretical problems

I'm going to implement HOG as my features descriptor. But there are some things that make me confused: For example: If we have an image with size of 10 x 20 If we want to compute the HOG of that ...
2
votes
1answer
75 views

Relative importance of a set of predictors in a random forests classification in R

I'd like to determine the relative importance of sets of variables toward a randomForest classification model in R. The ...
1
vote
0answers
12 views

How Does a Disparity in Number of Documents (Training Data Points) Affect Text Classification?

I have collected a fairly clean set of data (5,410 documents) to train a text classifier. I am now attempting to improve my classification success. (Note: When I trained/tested the classifier from ...
2
votes
0answers
59 views

My data lies on a linear plane

My purpose is to classify 3 classes from an EEG data. When I plotted my data on feature space in order to visualize, I found they lie on such a linear plane (please see my figures). Before plotting, I ...
0
votes
0answers
10 views

Training models for classification using different negative datasets

I'm working on a massively unbalanced binary classification task - Classification of given protein sequences as belonging to a certain (very small) class, or not. There are about 1,300 positive ...
-1
votes
0answers
22 views

What is the difference between a neural network and Deep neural networks? [duplicate]

Please i m looking for tutorial about neural networks and deep neural networks, -Architecture -Training -etc... Thank you :)
1
vote
0answers
24 views

Support Vector Machines - Kernel Functions/Soft Margin SVM

I had these questions in an exam today. State True or False and explain. If k1(.,.) and k2(.,.) are two valid kernel functions, then if h = k1 - k2, is h(.,.) a valid kernel function? A standard ...
0
votes
2answers
43 views

Splitting an imbalanced dataset for training and testing

I have a highly imbalanced dataset. My question is how to split the dataset for training and testing? I want to have a separate training set and a separate testing set. One idea I had is just to ...
2
votes
3answers
96 views

The value of adding the ROC graph if the AUC is given

I always see in papers that when they want to show how they classifiers performed, they provide ROC graph and the AUC score. Now as far as I know only the AUC tells how well the classifier performed, ...
2
votes
0answers
41 views

Time series prediction where each datapoint has a sequence

I am Computer Science major, and new to stats, so please bear with me and point me to the right direction if what I'm asking is pretty obvious. I have a dataset, where each data point consists of ...
0
votes
1answer
26 views

One vs All and One vs one in svm?

What is the different between onee vs all and one vs one SVM classifier?? Is One vs All mean = 1 classifier to classify all types /categories of the new image and one vs one mean= each type /category ...
0
votes
1answer
39 views

Automatic labeling of training set

I have once meet the following question, given a training set, is that possible to do the automatic labelling? In addition, if this training set consists of plain text files, is that possible to know ...
1
vote
1answer
54 views

How to interpret the number of k in k-nearest-neighbour classifier?

I have done some classification work using a k-nearest-neighbour classifier (kNN). And the classification performance is evaluated using cross-validation method. Some testing code from Matlab Help are ...
5
votes
3answers
235 views

Why is AUC higher for a classifier that is less accurate than for one that is more accurate?

I have two classifiers A: naive Bayesian network B: tree (singly-connected) Bayesian network In terms of accuracy and other measures, A performs comparatively worse than B. However, when I use the ...
0
votes
0answers
19 views

Classifier jars for java

I have a train file which has categorical features like IN JJ PRP_VBP VB NN PRP$ . . . The third column is the ground truth and can have value only out of ...
0
votes
0answers
23 views

Significance test for multiclass classifier

In a multiclass classification problem, I want to measure the significance of my classifier against the null hypothesis (in this case, chance level). In this paper, in section 3.4, for a binary ...
1
vote
1answer
60 views

building a classification model for strictly binary data

i have a data set that is strictly binary. each variable's set of values is in the domain: true, false. the "special" property of this data set is that an overwhelming majority of the values are ...
0
votes
0answers
25 views

How to reduce the dimension of a test data and make it uncorrelated?

I am working on classification of 16000 cell images. Each of them consists of 706 features related to intensity, morphology, colocalisation and texture of the cell. The train set consists of 11 ...
4
votes
1answer
128 views

Bayesian MLPs using the MCMC methods - any tricks of the trade?

Having used the NETLAB library for MATLAB to implement Bayesian Multi-Layer Perceptron (MLP) neural networks using MacKay's evidence framework, I am now experimenting with Markov Chain Monte Carlo ...
0
votes
1answer
23 views

Statistic test on percentage correct classified by emotion recognition

For a potential emotion recognition bachelor-project I was wondering what statistical test I have to perform when I get my results to test whether it's significant. I will be testing which combination ...
1
vote
0answers
26 views

Possible classification techniques to use when each feature is a probability distribution

I am working with some data where the features have a temporal aspect (e.g. how often does a feature occur between $t_{begin}$ and $t_{end}$). I am trying to build a binary classifier for this data. ...
0
votes
1answer
67 views

Good algorithms for feature extraction from images?

I am searching for some algorithms for feature extraction from images which I want to classify using machine learning . I have heard only about [scale-invariant feature transform][1] (SIFT), I have ...
0
votes
1answer
47 views

When to use accuracy and precision to evaluate binary classifiers?

I came a cross two ways to evaluate the performance of binary classifiers: accuracy and precision. When to choose each? And what are the advantages and disadvantages of each one?
1
vote
0answers
23 views

Statistical testing: Multiple classifiers, 1 domain. Would rANOVA be appropriate?

When comparing the performance of two classifiers over a single domain, in the context of a classification problem in machine learning, it is common to use a paired t-test, using the 10 average ...
3
votes
0answers
44 views

How to perform hypothesis testing for comparing different classifiers

I am trying to classify a small dataset (around 500 records) into two classes. I used various methods like SVM, Naive Bayes and k-nn classifier. Now, I would like to set the results from one of the ...
0
votes
1answer
33 views

Forcing a particular false positives rate in a learning algorithm

I have a learning algorithm that classifies points as 0 or 1 (haven't settled on which one to implement yet). Of the points I classify as 1, I want to ensure that the number of points correctly ...
1
vote
2answers
70 views

Dataset and papers for baseline [closed]

I'm doing a project about Topic Detection and Tracking in text. I need to perform a baseline so I can compare existing results with mine. I read some papers where they use datasets that are not so ...
1
vote
0answers
40 views

Machine Learning : Classification algorithm for very high dimensional data which is uniquely definable in a very small sub-space

I am new to machine learning, so forgive me if i am doing something absolutely absurd. I have a classification task (~100 classes) and have about 2 million training data points in a 2000 dimensional ...
0
votes
0answers
20 views

difference between text classification and categorization

Could any one help me to clarify the exact difference between text classification and text categorization in machine learning point of view. Thanks
1
vote
1answer
40 views

General questions regarding text-classification

I'm new to Topic Models, Classification, etc… now I'm already a while doing a project and read a lot of research papers. My dataset consists out of short messages that are human-labeled. This is what ...
0
votes
0answers
30 views

Which diffusion of latent Dirichlet allocation is helpful for assign the words corresponds to each topic?

In my corpus documents I have two different subjects. Which diffusion of LDA (asymmetric or symmetric) could help for assigning the words corresponds to Subject 1 and Subject 2 in my Topics? Here is ...
0
votes
2answers
86 views

Will Multivariate Gaussian classifier work for text classification?

So far i have evaluated mn Bayes and Bernoulli, so my question is if i take the counts of the words of each document and use them for assigning the document to the particular class will it work with ...
0
votes
1answer
29 views

Classifier weighted towards recall?

I have a classification problem where getting true positives is much more important than true negatives. To be clear, I know that roughly 10% of my population are actual positives, but I can assign ...
3
votes
0answers
36 views

Machine learning with ordered labels

The usual method for adapting binary classifiers like various SVMs to multilabel data is one-vs-all, which assumes that labels are independent and in case of a prediction error we don't care what ...