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11 votes
Accepted

Showing that Bayes classifier is optimal

The true error of a classifier $h$ is $$ \begin{align*} L_D(h) &= \sideset{\mathbb{E}}{}{}_{x,y \sim D} \Pr[h(x) \neq y] \\ &= \sideset{\mathbb{E}}{}{}_{x,y \sim D} \begin{cases} \Pr[y \neq 0|...
Yuval Filmus's user avatar
7 votes

Differences between SISD, SIMD and MIMD architecture (Flynn classification)

Flynn's taxonomy was defined by the great computer architect Flynn in 1960s. Though since that time there is an entire paradigm shift, so today it's better to understand these concepts with a ...
Ankit Maheshwari's user avatar
4 votes
Accepted

What method of collective recogintion to use for digits recognition?

The state of the art for digit recognition does not use collective recognition, competence areas, ensembles, or any of the other ideas you propose in your question. Instead, the state of the art for ...
D.W.'s user avatar
  • 162k
4 votes
Accepted

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

What you are looking for is called "on-line recognition". I have written my Bachelors thesis about this: Thoma, Martin. "On-line Recognition of Handwritten Mathematical Symbols." arXiv preprint ...
Martin Thoma's user avatar
  • 2,360
3 votes

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

A SVM classifier requires a fixed-length feature vector, i.e., all feature vectors must have the same length. There are multiple solutions: Pad out the strings to fixed length. Choose a different ...
D.W.'s user avatar
  • 162k
3 votes

What is the Best and easiest way to create a Classifer for Sentiment Analysis

This isn't the best way but it's simple and fast: preprocess the input with the Porter Stemmming algorithm (it's a process for removing the commoner morphological and inflexional endings from words ...
manlio's user avatar
  • 2,062
3 votes

how to interpret the coefficients of binary logistic regression?

I don't have the rep to comment, but the answer to your question is "sort of." It would take me too long to answer this question completely and with the proper care, so i will point you to a good ...
mm8511's user avatar
  • 206
3 votes
Accepted

Language Classification + AWS ML: what am I doing wrong?

There are probably multiple things wrong here. Features First, you don't tell us what features you have provided. If the only input you have provided is the word itself (e.g., the string ...
D.W.'s user avatar
  • 162k
3 votes

What is it called when you classify words into categories, but not by part of speech?

The name of the classification you are looking for is called Semantic field classification (https://en.wikipedia.org/wiki/Semantic_field). The sort of algorithm you are looking for falls under the ...
Andrei Alexandrescu's user avatar
3 votes
Accepted

machine learning classification with financial instrument/time series data

Consider that: a "sliding window" approach can be used with any standard regression / classification algorithm. E.g. given the following time series ...
manlio's user avatar
  • 2,062
3 votes
Accepted

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?

What I wanted to know is if there is a polytime algorithm (on the order of k) for determining this curve. If so, is there a known way to transform this curve into a function using some form of linear ...
Caleb Stanford's user avatar
2 votes

Is a KNN-Classifier memory intensive?

KNN is a memory intensive algorithm and it is already classified as instance-based or memory-based algorithm. The reason behind this is KNN is a lazy classifier which memorizes all the training set O(...
Osama Abdulhamied's user avatar
2 votes

Can I use machine learning to predict someone will buy something in a specific time?

Short answer: Yes it can be done using machine learning if you have features with sufficient information. Long answer: You can model this either as a multilabel problem (i.e Beer, chicken, pizza are ...
wabbit's user avatar
  • 170
2 votes
Accepted

Classification training data, but regression prediction

This is still a binary classification task. In the abstract, there are two ways to handle this: Most classifiers can output a predicted class and a confidence score (which indicates how confident ...
D.W.'s user avatar
  • 162k
2 votes
Accepted

What is the different between Dijsktra's algorithm and KNN?

What is the different between Dijsktra's algorithm and KNN? Almost everything. $k$ nearest neighbor is a classification algorithm. It stores a list of ...
Martin Thoma's user avatar
  • 2,360
2 votes

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

Yes, you can. The scheme you are thinking of is called the nearest-neighbors classifier. Read the link for more details. In many settings it turns out to be a quite effective classification ...
D.W.'s user avatar
  • 162k
2 votes
Accepted

How to find a possibility of match in Naive Bayes Classifier?

Let $A$ and $O$ be the events apple and orange (fruit). Let $R$ and $S$ be the events red and sphere. By Bayes' law, $$\Pr[A | R \wedge S] = \frac{ \Pr[R \wedge S | A] \Pr[A] }{ \Pr[R \wedge S] };$$ $...
Reinstate Monica's user avatar
2 votes
Accepted

How to show that i have significant improvements over the baselines?

Odds are, you can't. That's a judgement call, and it's notoriously hard to get other people to change their judgement. The path is to find new evidence or facts they might not be aware of; assemble ...
D.W.'s user avatar
  • 162k
2 votes

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?

I think that the proof in your provided link describes an algorithm that runs at $O(k^2\cdot n)$ time.
user3563894's user avatar
2 votes

Choose the best classifier to predict the label of strings of a regular language

My bet would go to a Recurrent Neural Network, as it closely models some (fuzzy, non-discrete) state machine as each character is output. A decent start to read up on RNNs for this purpose is to read ...
orlp's user avatar
  • 13.8k
2 votes

How can Machine Learning be used to find attributes/characteristics of graphs?

ML is not likely to be a good approach for these kinds of problems. It will probably perform far worse than a hand-designed algorithm. Current ML is not magic; it is just a form of pattern-matching.
D.W.'s user avatar
  • 162k
2 votes

Bible Verse division

In my opinion, this may be best approached as a sequence tagging problem, similar to part-of-speech tagging or named entity recognition. (So, this would be the seq2seq option, rather than regular ...
Sven Büchel's user avatar
2 votes

Find the exactly correct separating hyperplane of SVM when the data is not perfectly linearly separable

I think you can create a "half-hard" SVM problem. It will be like the hard SVM for positive labels (without the error term) but for negative example it will be the like the soft SVM (with ...
nir shahar's user avatar
  • 11.6k
1 vote

What kind of pattern recognition algorithm would Facebook use to detect suicidal users?

I would take march average to calculate several indicators from posts of the same user including but not limited to: - emotional-tagged words from posts (using available dictionary for this purpose) ...
Evil's user avatar
  • 9,495
1 vote

Scoring metric for machine learning method

To talk about the uncertainty in our model's prediction, we need to adopt a Bayesian framework. Here, our predictions $y^*$ are the mean of the posterior predictive distribution $\hat{y}^* = \mathbb{E}...
Nicholas Mancuso's user avatar
1 vote

Scoring metric for machine learning method

There are at least two possible interpretations of uncertainty: (a) uncertainty/confidence in the label that the network predicts; (b) uncertainty in the probability/confidence score that the network ...
D.W.'s user avatar
  • 162k
1 vote

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

I'm not an expert, but my understanding is the Recurrent Neural Networks are well suited to deal with sequences of data. This article gives a good (but possibly sensationalized) overview.
Joey Eremondi's user avatar
1 vote

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

You can padd your data. I can not delete or add more arbitaly data. It may make the result not correct. Don't make assumptions about neural networks. They can map any function, and if you don't ...
Thomas Wagenaar's user avatar
1 vote

Classifying objects by set proximity

One powerful and general approach is to write a probabilistic model that describes how colors are chosen, then apply maximum-likelihood estimation. The probabilistic model provides an expression for $...
D.W.'s user avatar
  • 162k
1 vote

Keywords for classification of 2D time series data?

The one-nearest neighbor classifier is very competitive for time series. http://www.cs.ucr.edu/~eamonn/ICML2006.pdf If you want code or data, I have lots of both. eamonn
eamonn's user avatar
  • 11

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