Methods and principles of building "computer systems that automatically improve with experience."

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Are there shape-matching scores that take into account multiple scales simultaneously?

Say you are determining how well your model of an object matches an image. To score this match, we can use e.g., the cross-correlation coefficient (CCC), giving an overall shape match. This works for ...
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0answers
14 views

Matching a query distribution to a family of template distributions

I was turning over a hypothetical question in my head: Suppose I have a set of template probability distributions, let's say each giving the probability of the occurrence of certain objects like ...
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2answers
304 views

How to calculate Fisher criterion weights?

I am studying pattern recognition and machine learning, and I ran into the following question. Consider a two-class classification problem with equal prior class probability $$P(D_1)=P(D_2)= ...
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27 views

What is the commonly used mehtod for measuring variance of accuracy mean using k-fold cross validation?

I know there are planty of questions about standard deviation, though I didn't find an answer tuned to my particular need and also I could really use your help! I'm performing 18-Fold Cross ...
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1answer
38 views

a challenge with linear classification and distance to origin? [closed]

I ran into a problem, when studying on linear classification. my prof. says: in a linear classification $y=w_0+w_1x_1+w_2x_2$ that depicted on following figure, distance of origin to decision ...
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11 views

How to create and format an image dataset from scratch for machine learning?

I've only worked with ML with .csv formats. I've worked with image formats too but only premade imagesets (MNIST,etc). If I were to create an imageset from scratch, how are the class labels typically ...
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13 views

graph classification task - multi label?

I have a data set in graph format representing semantic connection between terms. The data set is divided into clusters, each with several labels (not unique, or mutually exclusive, no set number of ...
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24 views

Learning from streams with concept drift in real world - how to handle missing class problem?

In currently delves into learning from streams with concept drift. As more I learn I think about how I can use learning algorithms on real data. Most of drift detection algoritms to evaluate is ...
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2answers
254 views

Compute the probability that the provided classifier label is correct

A binary SVM classifier provides a label $y_c^{(i)}$ for each $i$-th sample provided. This is not assured to be corresponding to its true label $y^{(i)}$, since the classifier could have computed a ...
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15 views

How to visualise the uncertainty of the classification?

I used SVM to do some classification, and SVM can output some probabilities (likelihood) value measuring how likely each data to be one particular class. For example, Data point 1: 90% (class 1) 5% ...
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2answers
41 views

Semi-supervised Learning Training

I have got some data partially labelled. Therefore, I would like to apply semi-supervised learning for this dataset. Basically, I trained the Support Vector Machine (SVM) using the data with labels ...
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21 views

Learning if instances from a dataset are part of the same subset

I was wondering if there are some well-known machine learning methodologies for subset learning. In other words, to learn if two instances are part of the same subset or not (boolean label?). One ...
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3answers
27 views

Prediction of features given predictor

I am working on a problem where my objective is to predict y given some features x1,x2,x3,...x8,x9 I solved this problem using some statistical and machine learning techniques like regression, trees, ...
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1answer
61 views

Relation between variance of eigenvalues and the effectiveness of PCA on the data

If the covariance matrix has eigenvalues $$\lambda_1 \ge \lambda_2 \ldots \ge \lambda_d > 0,$$ why is the variance of the eigenvalues, $$\sigma^2=\frac{1}{d}\sum_{i=1}^d (\lambda_i-\bar ...
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37 views

Support Vector Machine image classification in R

I'm looking for some direction for creating/running a support vector machine (SVM) classification on a multi-band Landsat image in R. What I have: Landsat 8 image with 8 bands plus a NDVI, and ...
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4answers
960 views

Introduction to machine learning for mathematicians

In some sense this is a crosspost of mine from math.stackexchange, and I have the feeling that this site might provide a broad audience. I am looking for a mathematical introduction to machine ...
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0answers
19 views

How to merge different predictive models training with different data sets?

Is there any good method to merge/consolidation different predictive models which were trained on different features but outputs the same goal. Example: Model 1 with features a + b + c (trained on ...
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1answer
61 views

Buiding Ensemble model

I'm new to ensemble model. Suppose I've KNN models like this - (in R) library(class) ...
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11 views

Importance of the norm of the weight vector in the perceptron algorithm

I have exhausted all possible searches online on the role of the norm of the weight vector in binary classification. The only information i am getting is that it prevents over-fitting. I don't see how ...
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14 views

How to include only true positives and false positives, that is ignore false negative classifications in a confusion matrix?

I have performed a 10 fold cross validation on my data set using binary decision trees. I've got 6 trees (to detect one of the six basic human emotions from facial data points) trained for each fold. ...
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22 views

Find repetitive patterns in matrices below

How can I identify the repetitive patterns from the matrices below? My problem is that the patterns in the matrix are different from matrix to matrix (dependent on the input data). I need some machine ...
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0answers
23 views

Apply trained MDS model to new data

I have both a distance matrix and the original vectors, and am using MDS (Multidimensional Scaling) with R to generate vectors in more dimensions for the data. With dimensionality reduction (for ...
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1answer
33 views

How to train a model when instead of a target we have a range where it is?

Often in machine learning we have a situation when target is numeric (real or integer). Each target comes with an associated input vector. The goal is to learn the mapping from the input vectors to ...
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1answer
61 views

Manifold learning: does an embedding function need to be well behaving?

I am trying to learn about manifold learning techniques; a family of methods in machine learning. According to this idea, there is a low ($d$) dimensional, hidden space where the real data generation ...
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31 views

Incorporating metadata to a supervised Topic Model

I have texts and their metadata and a response variable (how many times the text has been read). I'm interesting in finding out how the latent topics in the set of texts are related to the popularity ...
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1answer
77 views

What is “Prediction Accuracy (AUC)”, and how is it the number conducted in Machine Learning?

Here is the link in question: http://applymagicsauce.com/documentation.html When the Cambridge University Psychometric Center's "Apply Magic Sauce" defines how their ...
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22 views

machine learning to extend a matched sample (sanity check)

I'm a bit new to machine learning, but I want to try to use it in a project I'm working on. Specifically, I'd like to use it to identify a sample of potentially rare events. I'm not entirely sure if ...
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1answer
43 views

How could the predictive mean in a GP become negative when both the prior and the training target values are non-negative?

I am training a Gaussian process regression where the training target values are between 0 and 1 and the prior mean is the fixed zero function. The predictive mean sometimes becomes negative e.g. ...
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1answer
85 views

Which library is the easiest to start with for Deep Learning

I am quite proficient with Machine Learning libraries and now want to get into Deep Learning. I am even quite comfortable with neural networks as far as understanding back propagation algorithm is ...
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0answers
50 views

Combining bootstrap and cross validation

I recently read this paper: Estimating misclassification error with small samples via bootstrap cross-validation, by Fu et al. (BMC Bioinformatics, 2005). The authors talk about combining cross ...
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49 views

Combining two probabilistic predictions

I am solving a machine learning task in which I need to predict a label $\tau$ from input $\vec x$. The input $\vec x$ can be considered as two parts $\vec u$ and $\vec v$ ($\vec x$ can be thought of ...
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337 views

What does mean by PAC learning theory

I am new in machine learning field. I am studying a course of machine learning(standford university ) and I did not understand what's mean by this theory and what its utility. I am wondering if ...
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0answers
47 views

How to determine the accuracy of regression? Which measure should be used?

I have problem with defining the unit of accuracy in a regression task. In classification tasks is easy to calculate sensitivity or specificity of classifier because output is always binary {correct ...
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26 views

What do you do with outliers when developing statistical models?

I am a beginner so I have an extremely tough time dealing with outliers. I wanted to ask the community to help me understand rule of thumbs or anythng that would help me deal with these questions ...
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1answer
47 views

Validation of machine learning algorithms implementation

What are some techniques by which we can verify that a current implementation of a machine learning algorithm is correct? Is using the results of a benchmark dataset is enough?
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31 views

trouble with understanding neural network

Can anyone give an explanation for a page 422 from the The Elements of Statistical Learning. I couldn't understand the meaning of 'the least constrained model.' Paragraph and picture is shown as ...
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0answers
23 views

How do I learn algorithmic trading? [closed]

How do I learn how to set up an algorithmic trading system? I have taken Andrew Ng's Machine Learning course and am completing data sciences specialization on Coursera, am familiar with R and Octave. ...
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1answer
42 views

Why does hypothesis of SVM output 0 or 1?

Prof. Andrew Ng in his Machine Learning class says that unlike Logistic Regression, SVM outputs hypothesis as 1 or 0. But I don’t understand why SVM's behavior differs from that of logistic regression ...
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0answers
16 views

Test for autocorrelated variables

I would like to know if there is a good non-parametric test for detecting auto-correlation of one variable between all the observations of my dataset. I have 60 predictor variables for a statistical ...
3
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1answer
32 views

How to make a trained neural network “forget” an instance?

I am using neural networks for predicting the behavior of a dynamic system. A neural network is trained online using snapshots from the system's past. The system changes its state at irregular ...
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0answers
16 views

Anomaly Detection with very small number of positives [closed]

I am trying to detect anomalies in a population comprising of 10 features and around 90,000 observations. Past investigations have revealed 18 positives. Given limited data for supervised learning, I ...
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2answers
88 views

Is dimensionality reduction almost always useful for classification?

Is singular value decomposition almost always useful in practice for enhancing the predicative power of a trained classification model? E.x. A dataset for classification has 20,000 features. Run SVD ...
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47 views

using Cross Validation in matlab with neural networks

I want to make a cross validation on neural network, I tried to pass the labels to crossval function, with the help of ...
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1answer
31 views

What are the techniques to deal with classifying sparse categorical features?

Suppose I have a group of features each one is sparse with a few number of values (1-10) what are the required preprocessing steps required to avoid degradation of the performance of the classifier ...
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1answer
128 views

Machine Learning

I have been working on some self study "machine learning". Based on a few posts here, I wanted to make a program that "learned" via Bayes Law. I test it with some simple truth tables. It recalls the ...
3
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1answer
36 views

Cumulative match score

I have seen loads of graphs in papers of cumulative match scoring, but I can't find any information about what it means, or how it is created. A context that would be useful to see the explanation ...
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0answers
16 views

Generating a good training dataset for decision tree building

I am building a decision tree predicting the accuracy score of an image processing algorithm, based on a number of image parameters. I have identified 6 uncorrelated parameters that impact the ...
4
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1answer
115 views

Learning user behavior that changes over time

I am learning a model using SVM that will predict user behavior of some kind. Simplifying this model, each example in the feature space contains some features: $f_1,f_2,..,f_n$ and a class $a$ that ...
6
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1answer
41 views

Has there been a project to apply machine learning to generation of indices for books?

Generating an index for a textbook is a tedious task. Can one automate it with machine learning? Are there any references to previous attempts in the literature to do this?
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82 views

Semi-supervised classification with Rmixmod package in R

Semi-supervised classification with Rmixmod package in R. http://math.univ-lille1.fr/~biernack/index_files/articleJSS.pdf , a document on the Rmixmod R package, provides mathematical exposition of ...