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

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72 views

what are the alternative open source tools for PredictionIO?

PredictionIO is good to be enough for content discovery and recommendation but it seems it does not support classification. Then I should use a different tool then Prediction IO for my prediction ...
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63 views

Linear regression of 0/1 response (Fig. 2.1 of The elements of statistical learning)

In chapter 2 ESL book authors write: Let's look at example of linear model in a classification context They fit a simple linear model $g = 0.3290614 -0.0226360\cdot x_1 + 0.2495983 \cdot x_2 + e$, ...
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29 views

How to compare two clusterings generated by two clustering approaches

I am currently working on a modification of a clustering algorithm to suit my problem domain. I want to know which methods are available for me to compare the centroids generated from the two ...
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19 views

The ethics of using an optimal multiclass feature set for binary classification

I'm currently trying to find the best feature set/network architecture configuration for a binary classification problem, however to approach it via the usual means of building and testing does not ...
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14 views

Is time-delay embedding/attractor reconstruction used in some machine learning algorithm?

I try to model/forecast blood glucose levels from my diabetes diary, so I have to deal with some 5-7 daily measurements of estimated carbohydrates, physical activity, insulin doses and measured blood ...
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23 views

Interpreting R results, are the data multivariate normal?

I ran "mvn" using the "mclust" package in R using the following codes: mvn("EEE", data[,18:22], prior = NULL, warn= NULL) I am having trouble figuring out how to ...
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114 views

How to Use Neural Networks to Forecast Time Series Data with Predictor Variables?

I have browsed a lot of topics here, but the ones I see were all about forecasting a single variable, depending on its historical values. Whereas I want to predict a variable, by estimating a ...
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24 views

Is it true that decision trees can handle dependent features very well?

I have once heard that decision trees can handle dependent features very well, compared to e.g. Naive Bayes classifiers. However, I can't find any scientific source for that. So my question: is it ...
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1answer
42 views

Machine learning with categorical data: Can I delete examples?

I have a machine learning project that uses a bunch of features to predict a class that has categorical values. The possible values are: 1, 2, 3, 4, and 5. I'm interested whether the class has the ...
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11 views

Which terms are more standard: precision and recall or correctness and completeness?

I am familiar with terms like precision rate and recall rate from the machine learning literature, but recently I was reviewing a thesis which used the terms correctness and completeness. A quick ...
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65 views

Calculate rating/score based on multiple criteria to rank data

I extract data related to a movie by sentiment analyzing the reviews. Hence,extracted movie data contains average sentiment values (avg_pos and avg_neg) calculated over multiple reviews, total no of ...
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28 views

Stacked Generalization Ensemble Algorithm for regression

I am using stacked generalization(Rupert 1992) for combining multiple(8) heterogeneous base learners for regression. What I understand from the pseudo codes that Train the 8 learners on 8 instances ...
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16 views

Comparing densities of a feature for different classes when the feature is irrelevant to one class

Let us suppose that I have a number of features. I design pdfs for every feature and every class, some of them by smoothing some histogram of training samples, others just by introducing the prior ...
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80 views

Evaluating performance of machine learning models

I'm trying to predict when a location has enough wind to go sailing. I've built several models that look for correlations between different weather conditions and whether it ends up being windy X ...
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2answers
44 views

Instance weighing in libsvm/liblinear

I often use the instance weights with Libsvm for classification problems. http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/#weights_for_data_instances Does anyone know the details of the algorithm that ...
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2answers
62 views

How can I evaluate my model when the the testing data are too few and the generated results don't match testing data

I have a bioinformatic data set includes a very large negative examples (let's say 30000 examples) and just a few positive examples (let's say 150 positive examples). Since I need to feed an enough ...
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44 views

Has anyone publicly shared an implementation of RUSBoost in R?

There's no package available on CRAN, so I was hoping someone in the community had written their own function/package. I see it's been done in MATLAB, so I may just have to start with that and write ...
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41 views

R codes for variation of information criterion using “mclust”

I am developing model-based clustering. First, I developed model-based clustering in R using "mclust." Next, I wanted to take 75% of the sample, re-run model-based clustering and compare the ...
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3answers
43 views

The role of the bias terms in matrix factorization formulas?

I'm reading about matrix factorization for recommender systems. A basic matrix factorization model would be something like: $(p_i \times q_j ) + b_i + b_j$. That formula would compute the rating for ...
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22 views

Multi-class logarithmic loss function per class

In a multi-classification problem, we define the logarithmic loss function $F$ in terms of the logarithmic loss function per label $F_i$ as: $$ F = -\frac{1}{N}\sum_{i}^{N}\sum_{j}^{M}y_{ij} \cdot ...
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37 views

SVM versus Bayesian regression example(s)?

I am trying to track down examples where some basic problems have been tackled via both classical Machine Learning algorithms and more formal statistical methods. In particular, I'm interested in ...
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30 views

Hidden Markov Models relationship

I have a question regarding a small investigation that I have been conducting into the relationship between the length of observation sequence, T, on which two decoders (BCJR and classic Viterbi) ...
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44 views

The best way to solve particular classification problem?

I got training set (time series) of size approximately 2 million precedents {x,y}. Each x is a vector of size 20 and each y is a binary vector of size 10 like {1,0,0,1,1,0,1,1,1,0}. For a new input x ...
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18 views

How do you deal with different distance based features?

If I have a model where the set of features where a cosign distance measure makes sense for some of the features, and a Euclidean distance measure makes sense for the others for example using a BOW ...
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17 views

Hyper-parameters for pretrain and fine-tuning

When doing deep learning, in particular dnn, it's shown that pre-train each layer in a unsupervised fashion, then fine-tune the weights using the labeled data in a supervised fashion. My problem is, ...
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26 views

Examine SVM result by plotting histogram of decision values of training samples

I'm working for object detection(computer vision) and have some problems in SVM training. My training configuration is as below. Balanced training set (positive 3998/ negative 3998) The dimension of ...
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24 views

Choosing fold size for highly Imbalanced dataset + nested CV + svm

I am trying to classify a dataset with ~1000 points. 90/10 is the class ratio - super imbalanced. Here are the following steps I did: Use 20 relevant features from previous knowledge Remove highly ...
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3answers
185 views

What are the most popular artificial neural network algorithms for recognising the content of images?

What are the most used/popular artificial neural network algorithms for recognising the content of images in general? E.g. If the picture is of a person, dog, cat or a car. If the picture is a ...
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1answer
53 views

Whats going wrong in Implementation of this gaussian bernoulli RBM?

I have a problem in finding negdata value. In particular multiplying with sigma. Could someone help in representing this equation vishid*sigma*poshidstates + visbias in matlab. ...
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54 views

Classification using correlation

Given two correlation matrix (each $p \times p$), where each belongs to a different group, is it possible to classify a new sample into one of the group (based on the correlation matrix only)? What ...
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100 views

How does random Forest work for regression?

I am an absolute beginner in field of machine learning, I started doing titanic assignment in Kaggle and found(read some where) Random Forest is the best fit. I started reading about random forest and ...
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1answer
93 views

High Standard Deviation for Leave one out cross-validation?

I am using the leave one out cross-validation technique to evaluate my model. If the prediction on the test sample is right the output is 1 otherwise 0. So I have a array of N samples with 0's and 1's ...
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32 views

Is my understanding of how to calculate the reachability distance in local outlier factor correct?

Reading lof implementation at : http://www.cse.ust.hk/~leichen/courses/msc-it5210/lectures/LOF_Example.pdf the local reachability distance is given as : I don't fully understand this equation as ...
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18 views

How to use a set attributes of an entity at different time snaps to make predictive analysis?

The problem is to come up with a classifier for any task based on a set of attributes of an entity having different values at different times. For instance think about football players and their match ...
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21 views

Applying autoencoders for dimensionality reduction in audio: Why does this create a low-pass effect? [closed]

I've been playing around with framing audio data and training a single-layer autoencoder to find a dimensionality-reduced form (say 128-sample frames to 32-dimension frames). When I test the audio ...
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2answers
199 views

When to avoid Random Forest?

Random forests are well known to perform fairly well on a variety of tasks and have been referred to as the leatherman of learning methods. Are there any types of problems or specific conditions in ...
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1answer
49 views

Post hoc selection of important features in random forest?

I want to guarantee a parsimonious random forest (few features used). What are methods to do this? It was suggested to me to get the feature importance after the model was created, and then create a ...
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30 views

Validation accuracy larger than training accuracy

I was performing an experiment but got a higher validation accuracy than training accuracy. I've got a 39 mice data and performed leave one out cross-validation. The validation accuracy was 100%. But ...
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2answers
32 views

Accuracy of random prediction with non equal distribution

Assume that I want to predict the value of a variable that has three different states: a, b, and c. The chance that these variables have the 3 states is not equally distributed. Out of 10 trials, the ...
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2answers
58 views

Which property of count data make mean-variance dependency?

I have read about the fact that, there is dependency of variance on mean of count data.In most of cases they do variance stabilization transfomration as preprocessing step of data modeling. I wonder, ...
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1answer
57 views

Multi-class Confusion Matrix to Binary confusion matrix

i know the main concepts of data/text mining but i used them mainly in binary classification problems (just two classes). i am now dealing with a problem with 8 classes and i am atruggling how to ...
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24 views

How to deal with a feature relating to what type of expert labelled the data that becomes unavailable at point of classification?

Essentially I have a data set, that has a feature vector, and label indicating whether it is spam or non-spam. To get the labels for this data, 2 distinct types of expert were used each using ...
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1answer
69 views

why use Supervised vs Unsupervised given the class label?

Hi I have data set with a set of variables and known class labels. I am trying to compare why a supervised approach will work theoretically better compared to a unsupervised approach for ...
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71 views

MHT: Pre-Selecting statistical tests without Bias

Summary: The last formula boxed in red (which is a modified log likelihood from logistic regression) is a special non-differentiable loss function that is adapted to contain a Bonferroni correction in ...
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23 views

auto-steering using neural networks

I was hoping if anyone could point me in right direction, I want to implement a neural network that could steer an autonomous car, I have implemented basic classification problems before using single ...
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4answers
105 views

Interpreting conflicting results from Random Forest & Logistic Regression?

I am using SKLearn and Statsmodel in python to build a RF and Logistic Regression, respectively. I have a feature that the RF indicates is important (feature importance of 0.202, closely behind #1 ...
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1answer
39 views

How should the precision/recall be calculated for classes in datasets with NO true class instances?

I have built a classification model to recognise a class and I have evaluated it on several datasets. The problem is that some of these datasets do not have any true instance of the class in question, ...
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4 views

what is the meaning of the Samples in NER?

I would like to know in NER (Named Entity Recognition ) problem , which concept should be considered as samples? each token as a sample? or each sentence ? or each Named Entity should be considered ...
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29 views

What is the difference between Contrastive divergence k and persistent contrastive divergence algorithm?

As per my understanding Contrastive divergence k is obtaining v(k) after k steps of gibbs chain. Persistent contrastive divergence is obtaining v(k) independent of v(0). I am quite confused with the ...
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29 views

Which statistics to use in order to understand a dataset?

So I have a dataset that I will use to train a bunch of classifiers. I need to do that for my thesis. However I'm not sure which statistics are good to use to better understand the dataset and the ...