Questions tagged [machine-learning]

Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.

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231 views

Feasibility of a neural network fitting a specific multivariate quadratic function? [duplicate]

I have run into some problems when trying to train a network that fits some multivariate quadratic function, or the Euclidean distance between 2 points in a 3-dimensional space, where they are 'pretty ...
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0answers
16 views

Robust method to extract “pure” part of a variable

I am trying to perform a multi linear regression model: $$y_i = β_0 + β_1x_{i1} + β_2x_{i2} +... + β_px_{ip} + ε_i$$ where $$x_{i1}, x_{i2}, ..., x_{ip}$$ are highly correlated with each other (VIFs ...
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2answers
75 views

What is the best machine learning approach for this problem?

Please forgive my ignorance, however I would like to explain this problem and get some advice on how to approach it. Let's say that I have the following training inputs, where ...
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82 views

Should cross-validation be used to provide the final parameters, or just to compare models?

In Andrew Ng's Coursera class on Machine Learning, we learned to use a Gaussian distribution $p(x)=\prod^n_{j=1}p(x_j,μ_j,σ^2_j)$ to detect anomalous examples when $p(x)<\epsilon$ where $x_j$ are ...
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1answer
595 views

What is the difference between using single multi-output NN and multiple single-output NNs

Pretty new to machine learning and would like to know what is the difference in model accuracy between using single multi-output NN and multiple single-output NNs all used in tandem (OvA and OvO)? Eg....
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54 views

Before running a ridge regression model, do I need to preform variable selection?

I am currently constructing a model that uses last year's departmental information to predict employee churn for the current year. I have 55 features and 318 departments in my data set. A good ...
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2answers
182 views

step by step tutorial for newbie

I'm looking to join the field of statistics and more exactly to forecasting. I'm a software developer and I just started playing with R. Can you recommend me some tutorials related to forecasting, ...
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96 views

Is it correct to evaluate Neural Network after a fixed number of batch-updates, rather than at the end of epoch?

I'm training a neural network on a number of datasets of different size with a fixed batch size and an exponential learning decay. Normally, I would evaluate model performance, save checkpoint and ...
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2answers
566 views

Naive Bayes for Spam detection

I am studying few examples of simple Naive Bayes for Spam detection. I had a question it, but I am unable to find it in any of the examples. I was wondering, what will happen if a word appears ...
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1answer
981 views

How to define silhouette for one cluster?

I want to compare two clustering algorithms. I took data that the first algorithm gathered in one cluster. The second algorithm gave 3 clusters for the same points. In order to compare the results, I ...
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269 views

Is a covariance matrix defined through a Gaussian covariance function always positive-definite?

When using Gaussian processes, the covariance matrix $\mathbf{\Sigma}$ is often defined via a covariance function $K$ as follows $$ \mathbf{\Sigma}_{ij} = K(\underline{x}_i, \underline{x}_j) $$ where $...
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1answer
589 views

Nested cross validation from a practical perspective

I'm very confused about nested cross validation works . I have seen that nested cross validation is necessary to split parameter selection and model selection, since using the test set to both ...
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16 views

Dropout and feature visualisation

If we use drop out in our CNN, this will lead to features being more displeased and less concentrated on specific neuroma. Won't this make feature visualisation very difficult since we can't locate ...
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1answer
47 views

What is the reasons for a model to have a high cross validation score and yet underperforms on unseen data?

I have a model that is based on an experiment collected on 100 subjects. We are testing the model as follows: Record raw data from the subjects For each subject, compute the feature from the raw data ...
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0answers
40 views

Gaussianity and Whitening in ICA - The feeling and intuition behind it

I understand what ICA does at a high level but in the cocktail party problem context. All the examples, articles I have read take a similar problem to explain ICA where the aim is to derive the ...
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1answer
106 views

Assessing model performance of stochastic algorithm

I'm looking at how I currently evaluate my classification models and wondering if it could be improved. I've got a stochastic algorithm (Genetic Programming), which for non-classification problems is ...
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1answer
2k views

Large data variable selection

I'm looking for some methods of variable selection on large datasets.The number of variables are around 30-40, but the number of observations is quite large (around 36000000) Any methods which I ...
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2answers
957 views

Are the kernel parameters and the regularization parameter correlated in SVM?

Im trying to learn some hyper-parameters for SVM classifier, I want to know if there is any correlation between the kernel parameters and the regularization parameter - C,. because if not i can then ...
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1answer
601 views

# parameters: 4th order polynomial regression in 5 dimensions

I read that a 4th order polynomial regression in 5 dimensions amounts to 15625 parameters. However, I cannot figure out the way this is calculated. Can somebody help me out?
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1answer
131 views

Approach to classify text using machine learning

I am trying to find the best approach to this problem. Consider that there is a type of text document, for instance a letter. I will refer to this as the ...
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1answer
975 views

How do I train sklearn model to predict square of an integer

I created sample training data with set of random numbers and their squares. But when I predict square of a new number, none of the sklearn models are predicting it correctly. Given below is my sample ...
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1answer
353 views

liblinear one vs rest learn parameters

Liblinear (http://www.csie.ntu.edu.tw/~cjlin/liblinear/) does not support for probability estimates. Say I have three classes C1, C2 and C3. I want to learn the model paramters for each 'one vs rest' ...
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1answer
170 views

Generative Adversarial Network: How to find the most similar image to the output within the training samples?

How can one find the most similar image in the input data training set to the output of a tensorflow implementation of Deep Convolutional Generative Adversarial Networks? If I use DCGAN, faces will ...
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1answer
44 views

why flat priors and noiseless data are required for MAP learning

The brute force Maximum A Posteriori estimation involves computation of posterior probability for all values of $\theta$ and then we choose the value of $\theta$ that maximizes $P(\theta | D)$. Right. ...
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1answer
85 views

What to conclude for the data-set when the variance for principal components is too low or too high?

I am working on analysing and visualizing a dataset having 12 features and came across PCA. I reduced the dataset to 2 principal components which together explain a variance of 18%. I was able to plot ...
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1answer
3k views

R: Trouble using SMOTE package “invalid 'labels'” [closed]

Using SMOTE package from DMwR library. After loading the data frame, I try to perform sampling as follows : ...
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1answer
294 views

AdaBoost algorithm question

In the boosting algorithm,AdaBoost ,those observations which were misclassified by the classifier in the (m-1)th step have their weights increased in the mth step, and those which were correctly ...
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313 views

Clustering using Random Forests Results

I used a RF model to predict a rare event. After testing using multiple iterations, I settled on a model which provided decent results. I tested this model on a validation data I had kept aside before ...
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1answer
151 views

Appropriate statistical analysis to use

I have built and tested a computer application, which involved two participant groups (Group-A with existing knowledge of databases and Group-B without knowledge of databases). I was required to apply ...