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Questions tagged [classification]

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Does it make sense to use Bayesian Network to understand feature correlation of clusters created with K-means?

My project idea is to create clusters of typical rooms for hotel customers, indicate which rooms are similar to the one they are looking for and let them understand why they are conceptually similar. ...
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What is meant by A determine BC in functional dependency. How the validity of this statement will be checked

We use notation A determines BC in a database for functional dependency. Same way we use equations in mathematics which shows dependency of variables. We have inference rules in logics, functions in ...
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Find the exactly correct separating hyperplane of SVM when the data is not perfectly linearly separable

I am thinking about the following case where the data in region 1 is always positive and the data in region 2 is always negative, but the data in region 3 can be both positive and negative. Are there ...
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What are the confusion matrix values?

I'm currently going through past paper questions and was wondering if I could get some help answering this one? 'Consider a classification model which is applied to a set of records, of which 100 ...
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Does Linear Discriminant Analysis make dimensionality reduction before classification?

I'm trying to understand what LDA exactly does when used as a classifier, i've understood how the dimensionality reduction works and i've understood that the classification task is carried out with ...
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1 answer
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SVMs - Fat (Margin) Boundary: Why is $\max\frac1{||\theta||}=\min \frac{ ||\theta||^2}{2}$?

I am trying to understand SVMs in depth watching lectures from MIT. The professor to reduces the classification problem into an optimization problem. To do that, he first defines the decision and ...
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1 answer
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LSTM : What should I do if I am always getting an output too close to one value?

I am training a model for ham and spam classification using LSTM. I am indicating the spams as 0, and the hams as 1. However, the dataset has much more hams than spams, so I tend to get an output very ...
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Classification of the Summit supercomputer

Can we classify a supercomputer in more than one group? For example, Flynn's classification, classification according to topology, classification according to memory access. For the Summit ...
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What are Volterra classifiers

I want to learn about Volterra classifiers in-depth to understand the following papers Papers https://openaccess.thecvf.com/content_cvpr_2014/papers/Kang_Convolutional_Neural_Networks_2014_CVPR_paper....
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ML Algorithm for getting top pick in each sample

I have a dataset of streets - and each street contains several houses. ...
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2 votes
1 answer
39 views

Bible Verse division

I'm working on a project compiling various versions of the Bible into a dataset. For the most part versions separate verses discreetly. In some versions, however, verses are combined. Instead of verse ...
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classify location of the expiry date on drug label and lot number

Is it possible that using the Machine Learning classification model we can classify/predict the LOCATION/ORIENTATION of the lot number and expiration date on different vials label? If yes, possible ...
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2 answers
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How can Machine Learning be used to find attributes/characteristics of graphs?

I am aware ML is not necessary for many graph classification problems (as the graph theorists have many clever solutions), but I'm specifically interested in ML approaches to these types of questions. ...
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Image classification with zero data

Given an image of a biology diagram, I would like to classify the diagram into these 4 categories: Plant Animal Cell Anatomy However, I don't have any training data. I would like to avoid the ...
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1 answer
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Mapping categorical data in K-nearest neighbour

I have a data set which contains categorical data, for example: ...
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4 votes
1 answer
93 views

Classifying partially labeled data

I have 1D data for binary classification. Data includes about 10000 samples and each sample has the length of 120. Data is only partially labeled (for about 20% of samples, I am sure about the label) ...
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Classification accuracy based on top 3 most likely classifications

My goal is to recommend jobs to job seekers based on their skill set. Currently I'm using an SVM for this, which is outputting one prediction, e.g. "software engineer at Microsoft". However, consider ...
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Hypothesis space in AdaBoost or general Machine learning

I was curious about the following: in most learning algorithms, when an algorithm is said to learn a concept class $C$ then the algorithm outputs a function from the hypothesis space $H$ and often ...
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Examples of Regular, Context-free and Context-sensitive languages

Assume the languages: $$ a) \, L_1 = \{ w \in \{b,c \}^* | \, w \, \text{contains 'bbc' as substring} \} $$ $$ b)\, L_2 = \{ 1^k 0^m 1^m | k,m \in \mathbb{N} \} $$ $$ c)\,L_3 = \{ w \in {0,1}^* | \,...
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Algorithm for out-of-area point classification

I have a device that sends its coordinates every 30 seconds. When I receive the coordinates, I classify the point as either belonging to (ie being inside) one of a number of predefined areas (so I ...
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What is the purpose of standardization in machine learning?

I'm just getting started with learning about K-nearest neighbor and am having a hard time understanding why standardization is required. Reading through, I came across a section saying When ...
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-1 votes
1 answer
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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 ...
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1 answer
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SVM with a priori information about class probabilities

Given are two 2-d sets, each with its own bivariate normal distribution. I need to build an SVM classifier. The a priori probabilities of each class corresponds to the size of its set (20/50 for the ...
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642 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 ...
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5 votes
1 answer
81 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 ...
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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 ...
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3 votes
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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 ...
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1 answer
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Choose the best classifier to predict the label of strings of a regular language

I have to tackle this problem: I have some strings that are my training set. These strings belong to a regular language corresponding to a deterministic finite automata (hidden namely I don't now it, ...
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1 vote
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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 ...
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1 vote
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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. ...
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5 votes
2 answers
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Given $k$ points in $n$-dimensions, such that $n\geq3$, is there a polytime algorithm for finding a curve that splits them into 2 sets of points?

So in this math exchange question I asked, it was proven that for $n>2$ dimensions, you can always find a curve that separates $k$ points in $n$-dimensional space into $2$ arbitrary sets that you ...
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1 answer
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How to show that i have significant improvements over the baselines?

I had review feedbacks regarding my recent publications and reviewers argued that the improvements are not significant over the baselines. I tried my classification algorithm on some image datasets ...
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1 vote
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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 ...
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1 vote
2 answers
145 views

The well-known classifiers that can be trained/tested in linear time [closed]

I am interested in collecting the list of the classifiers that (depending on their setting) can have linear time complexity (both in training and testing step) with respect to the number of samples $n$...
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1 answer
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How to find a possibility of match in Naive Bayes Classifier?

My math level is very very poor so I can't get the statistics. Can anyone explain in simple words? I.e. if I have frequency data: ...
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1 vote
0 answers
50 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 $P,Q,R,S$ ...
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2 answers
927 views

What is a monotone dataset and monotone classification?

Classification algorithms, such as k-Nearest Neighbors, are well known in machine learning area, but I faced this new expression Monotone classification and I wonder what does it stand for. I guess ...
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1 vote
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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 ...
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1 answer
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Feature selections : Still a high dimentionality

One of the advantage of using a features reduction/sub feature selection is to avoid a high dimentionality. The most known method is the Forward selection, where it finds the best combinations of ...
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185 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?...
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2 votes
2 answers
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What kind of pattern recognition algorithm would Facebook use to detect suicidal users?

Facebook announced that it would employ a machine learning "reporting process using pattern recognition in posts previously reported for suicide" (https://newsroom.fb.com/news/2017/03/building-a-safer-...
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1 vote
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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....
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0 votes
1 answer
1k views

Can a KD tree be used as a decision tree through nearest neighbor queries?

If I were to construct a KD tree representing a sufficiently dense space, could it be used as a decision tree by querying it for the nearest neighbor to the point to classify?
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1 vote
0 answers
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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 ...
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5 votes
1 answer
272 views

What is a good approach to symbol identification/recognition given a path, instead of raster data

Excuse any mistakes in my description as I'm new to ML. But I have an application that takes user input to generate paths/curves (All symbols are single paths) and I would then like to attempt ...
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1 vote
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Which Machine Learning algorithm should I use for gender tagging of words in NLP? [closed]

I have a dataset of about 26,000 words along with their gender tags [m, f or any]. Which ML algorithm should I use for Gender Tagging/Classification purpose. How should I go about it? What should be ...
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1 vote
2 answers
839 views

Scoring metric for machine learning method

For a machine learning method X (Deep Neural Nets variant), which performs classification tasks. In the output layer, for every label method, ...
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1 vote
1 answer
593 views

how to interpret the coefficients of binary logistic regression?

I'm working on a kNN classifier to classify whether a text is written by a man or a woman on the basis of the most frequent words. However, a kNN doesn't show which features were the most important in ...
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1 vote
2 answers
200 views

How to use Neural Network classification if data not same size?

I have data like this. [0 1 0 1 0] [0 1 0 1 0 1 1] [0 1 0 1 ] [0 1 0 1 0 1 1 1 1 0] ... I want to classify with Neural Network but my data different size . I can ...
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2 votes
1 answer
518 views

How to tackle different sample size in the training set in SVM

I have to train a SVM for a classification problem. I have some strings that are the paths in a deterministic finite automata (DFA). If the alphabet is -01- then possible strings are 011101110 or ...
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