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Questions tagged [classification]

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2
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1answer
32 views

k-means clustered data: how to label newly incoming data

I have a data set with labels that were produced by a $k$-means clustering algorithm. Now there is some data (with the same data structure) from another source and I wonder what is the most sensible ...
0
votes
1answer
15 views

Dimension Reduction - Which feature should remove to reduce the dimension of the matrix

Let's suppose that we have the following 2 tables: If we want to reduce the dimension by one(in every table) which feature we should remove and why ? I am confused about the way that i should work ...
-2
votes
1answer
52 views

classifier accuracy

I’m developing a mutual information based classifier, the output of the classifier is {{0,4,5,6},{1,2,3},{7},{8},{9}} and the correct decision output is {{0,1,2,4,5,6,9},{3},{7,8}}. How to compute the ...
7
votes
0answers
1k views

What machine learning method for diabetes prediction SW?

I'm thinking of an application for diabetics, that, given previous values of blood glucose and insulin dosage, predicts the glucose level for the next few hours. I know a few things about neural ...
4
votes
0answers
137 views

What are the best features to identify heads from any angle?

I want to automatically track heads in CCTV records. Sometimes I need to re-identify heads because of multiple heads crossing each other. So I continually need to extract features from tracked heads ...
4
votes
0answers
162 views

some kernel and greater margin, how this occures?

I read following notes, and couldn't get it. any idea or hint would highly appreciated. a SVM classifier using a second order polynomial kernel. The first polynomial kernel maps each input data x to ...
3
votes
0answers
416 views

What is the activation function, label and loss function for Hierachical Softmax

Several papers(1 (originator), 2, 3) suggest the use of Hierachical Softmax instead of softmax for classification where the number of classes is large (eg many thousand). I haven't been able to get ...
3
votes
0answers
58 views

Should Expectation Maximization take into account the Naive Bayes' independence assumption?

Should the independence assumption on which the Naive Bayes (NB) classifier is based, be taken into account when applying Expectation Maximization(EM) to infer missing values? The Naive Bayes ...
2
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0answers
25 views

Classify/Distinguish between 8008 binary grids, with 13 queries

I have $8008$ binary grids of size $6 \times 10$ (they are all grids with the property described below), which I want to distinguish between with at most $13$ queries. A query will determine if the ...
2
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0answers
51 views

Two classes of documents. Find weighted relations between them

I have an NLP problem and a potential solution, but I’m a bit green here, so I’m looking for some validation or alternative suggestions. Background I have two types of documents: one is a set of ...
1
vote
0answers
20 views

Classifying a problem involving matching bit arrays

First explaining the "reverse" use as a background: There is an array A which contains N boolean values There is an array B which contains N boolean values I start iterating over array A and for ...
1
vote
0answers
39 views

Why do reviewers always want to compare the method with deep learning baselines and Big data?

I work on the topics of sparse coding (SC) and dictionary learning (DL), in which classification is not the main goal, but the discriminative power of the representation is one of the concerns. ...
1
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0answers
57 views

Why don't Artificial Neural Networks Commonly Diverge?

Introduction: I'm using divergence here as to mean that the gradient is getting further and further from zero in stochastic gradient descent. I've written my own feed-forward neural network and tried ...
1
vote
0answers
22 views

Attribute Selection for minimum number of clusters

I have a table consisting of some headers $P, Q, R, S$ (shown in blue in Table 1). According to the headers, the column $T$ is populated using some predefined logic. Now, any of the headers $P,Q,R,S$ ...
1
vote
0answers
70 views

Understanding Time Series Data for Classification

I have collected data from numerous volunteers driving a simulator in 8 different scenarios (classes). A volunteer drives in a map for 4 minutes in one scenario (one experiment), then he drives in the ...
1
vote
0answers
26 views

Should I normalize values not bigger than 1

I have a question regarding a normalization of values especially in the case of image processing features classification. What if have a series of values that will never be bigger than 1. A = 0.004 0....
1
vote
0answers
44 views

Question about (in)dependent Haar-features and (Ada)boosting

I have an old exam question for my pattern recognition course which is stated as follows: Consider a pool of Haar features, determine if these Haar features are independent or not. Is it a problem ...
1
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0answers
64 views

Problem with the motivation of penalized logistic regression

The following is a motivation for penalized logistic regression in some lecture notes I'm following: Although the cost-function for logistic regression is lower bounded by 0 we get issues if ...
1
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0answers
32 views

Classification with optional/catchall attributes

Context Let $S$ be a set of objects, each object $S_k$ containing a set of attributes $A_k\subseteq A$, where $A$ is a global set of attributes. Suppose each attribute $a_k\in A$ can take on integer ...
1
vote
0answers
16 views

How do you set the number of words in the visual dictionary?

How do you set the number of words in the visual dictionary? I tried to understand the different steps to obtain the visual dictionary first: Feature detection: Examines every pixel to see if there ...
1
vote
0answers
166 views

Knowledge Vault - Please explain the local closed world assumption

Background I'm currently reading a paper on the google knowledge vault here : http://www.cs.cmu.edu/~nlao/publication/2014.kdd.pdf. I'm having trouble with the Local Closed World Assumption (LCWA). ...
1
vote
0answers
50 views

Why naive Bayes performs better?

I have found that naive Bayesian classifier performs much better than classification using mixture of multivariate Gaussians. Here is the problem: I have a set of objects with attached features (10 ...
1
vote
0answers
99 views

How to train a Conditional Random Field/Markov Random Field Model for Object Classification in images given the features?

I want to classify superpixels in a image using a Markov Random Field/ Conditional Random Field model but have found no place that can help me with this (references don't even show how the network is ...
1
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0answers
77 views

Similarity based document classification compared to the user profile ratings

I need to understand a distinction to check if I understood a document classification problem right. Given a training set of documents with ratings, that a user has given, let's say rating $r_{k} \in ...
1
vote
0answers
34 views

How to make logical inference from simulated data

I have data collected from a computer simulation of football games which seem to have recurring patterns of the following form. if madrid plays arsernal and the match ends under 3 goal, then on ...
1
vote
0answers
100 views

General object recognition versus specific object recognition

I have a question about the difference between general object detectors and specific object detectors. By specific object detectors, I'm referring to classifiers/object recognizers that are built to ...
1
vote
0answers
253 views

N-ary (NOT binary) Gentle Boost algorithm?

I know Gentle Boost, an adaption of the AdaBoost algorithm, can be used for binary classification. However, I need to do $n$-ary classification. How do I modify or extend the GentleBoost algorithm so ...
0
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0answers
9 views

How does the Random Forest classification function

I was going the through Random forest classification trying to understand it and I stumbled on two equation and I was wondering if anyone knows their name. what are the names of the theorms or ...
0
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0answers
49 views

Random Forest - Conditional Permutation Importance

I've been looking for the most unbiased algorithm to find out the feature importances in random forests if there are correlations among the input features. Besides the most commonly preferred ...
0
votes
0answers
44 views

Resource allocation / optimization

At work I stumbled across this problem of allocating resources: We are given a set of objects belonging to one of seven possible classes (multiple objects per class are allowed). We distinguish ...
0
votes
0answers
8 views

About cross-entropy loss

Is there a classification scenario with cross-entropy loss such that the loss as a function of the predictor/neural net's parameters is a function s.t it satisfies the properties of (a) having a ...
0
votes
0answers
128 views

(Percision & recall) Vs (Accuracy)? which one do I have to consider?

I am running several machine learning classifiers to predict something from my data. If I visualized the precision and recall tables as a result, is it enough to get clear idea about the proposed mdel?...
0
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0answers
49 views

Genetic algorithms, Pittsburg - Reach a decision from a set of rules

Consider a binary classification problem. In the Pittsburg approach each member of the population represents a set of rules. Each rule encodes information regarding the data features (that is, the ...
0
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0answers
136 views

Support Vector Machines vs K-Nearest Neighbors

Let's say we have trained a Support Vector Machine with a Gaussian Kernel. When we feed our model an example, it classifies it based on its similarity to landmarks (distance to examples in our ...
0
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0answers
828 views

Classifying responses into yes/no

So my problem is as follows: I get responses (such as "yeah whatever", "yes do it", "no don't do it", "nah", "yeah do it" etc.) and I need to classify them into either "yes" or "no" i.e. a binary ...
0
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0answers
231 views

Optimal Design of Cascaded Classifier

Consider a cascade of classifiers and a binary classification task. Cascade consists of some number of strong classifiers (n) each of which consists of some number of weak classifiers (m_i, where i = ...
0
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0answers
39 views

Finding number of clusters in a dataset

I am learning the basics of data classification using competitive learning, and am somewhat confused regarding the way this is implemented. I understand at the start an amount N of prototypes is ...
0
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0answers
78 views

Learn feature value range for a classification

Which domain does this problem belong to? Given a set of products some are classified as cheap and some not. The task is to determine the price range (probabilistic) for cheap products. Supervised ...
0
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0answers
38 views

How to discern devices based on their traces?

I would greatly appreciate your advice on following machine learning problem: I need to train a classifier to learn a device's behavior. The device itself can be observed under different operating/...
0
votes
0answers
252 views

Ways of object recognition in computer vision

In the field of computer vision, we talk a lot about this process of feature detection-description-matching as a way of recognizing objects. But on the other hand, there's also talks about object ...