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

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About writing a machine learning paper

I applied support vector machines to a relatively small dataset. I used relatively simple techniques, and achieved publishable results. Now, when already writing the paper, I got an idea, which would ...
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4 views

Which model approach for data with timings and signals

I have a data set of times, signals and their values. The signals have values from A1 to A6. The first 25 data points of the record are as follows: ...
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8 views

Auto tune PID loop using linear regression

I am sure most of you are familiar with PID loop. Let look at an example to help me explain what I want to do. Let say I want to tune a temperature control PID, for home air conditioning. My apartment ...
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15 views

Do we still need to do feature selection while using Regularization algorithms?

I have one question with respect to need to use feature selection methods (Random forests feature importance value or Univariate feature selection methods etc) before running a statistical learning ...
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1answer
17 views

Mathematical Basis behind inflation of Standard errors of Regression estimates due to multicollinearity

We know that due to multi-collinearity, the standard errors of beta estimates get inflated. But what is the mathematical basis to it? I am looking for some mathematical relationship or something to ...
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9 views

Map of activated brain regions for special feature extraction method

I have read the following paper: "Feature Extraction for fMRI-Based Human Brain Activity Recognition". The most useful point for me is the new method of extracting features from fMRI images. It ...
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7 views

Obtaining a HOG feature vector for implementation in SVM in Python

I am new to sci-kit learn. I have viewed the online tutorials but they all seem to leverage existing data (e.g., digits, iris, etc). I need the information on how to process images so that they can ...
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1answer
13 views

How to do crossover and mutation in one GA iteration process?

I am learning genetic algorithms. I am trying to demonstrate one GA interation process for the problem as follows: X, Y and Z are the three integer variables ranges between 0 to 3, and there are ...
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7 views

Predicting nucleotide sequence efficiency

I am new to machine learning and I am wondering whether it would be possible to use my available biological data for clustering. I want to find out whether a group of DNA sequences can be clustered ...
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21 views

Difference between regression and performance plot of Artificial neural network in MATLAB

I am having problem understanding regression and performance plots of ANN. My data consists of 13 inputs and 3 outputs. Parameters used for simulation can be found here. The problem I am facing is ...
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33 views

Statistics Questions on Roulette Game [on hold]

I have a few statistics questions and wanted to see if someone could give the right reasoning. Let's say there is a roulette game and a roulette wheel with equal no. Of red and black slots. The ...
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9 views

how to make or prepare range file in svm-scale in libsvm using matlab

Respected all, I am using LIBSVM, for scaling the input data svm scale function is used. The syntax is 'svm-scale -l -1 -u 1 -s range train > train.scale' or svm-scale -s scaling_parameters ...
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27 views

Logistic Regresion / SVM / Random Forest Implementation in Matlab

I would like to implement (L2-regularized) Logistic Regression, (L2 regularized) SVM and Random Forest for multiclass classification in Matlab (without using a toolbox or the corresponding functions ...
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1answer
12 views

Fit multidimensional feature into design matrix

I'm having trouble understanding how I can have a multidimensional feature in my design matrix. I understand the concepts of PCA, but I'd rather avoid it. I have the feeling that I'm missing out on ...
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12 views

Is value iteration considered a reinforcement learning Algorithm or planning algorithm?

Recall value iteration: $ \text{Initialize $V_0(s) = 0 , \forall s \in S$} \\ \text{Repeat until convergence},\{\\ \quad \text{Given value function $V_i(s), s \in S$ for iteration $i$ do:} \\ ...
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1answer
22 views

Why (and when) does one have to learn the reward function from samples in reinforcement learning?

In reinforcement learning we have a reward function that informs the agent how well its current actions and states are doing. In a some what general setting the reward function is a function of three ...
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17 views

Random forest vs Adaboost

In section 7 of the paper Random Forests (Breiman, 1999), the author states the following conjecture: "Adaboost is a Random Forest". Has anyone proved, or disproved this? What has been done to prove ...
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31 views

Vectorization of Cross Entropy Loss

I am dealing with a problem related to finding the gradient of the Cross entropy loss function w.r.t. the parameter $\theta$ where: $CE(\theta) = -\sum\nolimits_{i}{y_i*log({\hat{y}_{i}})}$ Where, ...
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35 views

Treating missing data in voting pattern analysis

I'm trying to analyze voting patterns of Ukraine's parliament deputies. I scraped all the data on their voting during last session. Each data entry has following information: Deputy name, date, bill ...
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33 views

Maximizing oldest possible average date of dataset [on hold]

Let's say we have a dataset by date and dollars: ...
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10 views

Classifier for mixed data points

I have a dataset looking like this: Item: 1 -> Label: 50, Score: 0.0015272063901647925, FALSE Item: 2 -> Label: 50, Score: 0.012096011079847813, TRUE Item: 3 -> Label: 50, Score: ...
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18 views

k-means random initialization for very-large dataset, is it good enough?

I've got a question in clustering using random k-centers. I ran the k-means algorithm for 10 iteration, for some 100 rows taking 9 random initialization of centroids from the data set itself. The ...
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35 views

MLP: Classification vs. Regression

Abstract I am teaching myself about NNs for a summer research project by following an MLP tutorial which classifies the MNIST handwriting database. I want to change the MLP from classification to ...
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1answer
43 views

Is this data from machine votes or human votes? Opinions appreciated!

A friend recently entered (but lost) an online competition where the winner was chosen based on total votes. Only one vote would register per IP address so as to discourage multiple votes coming from ...
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1answer
23 views

Random Forest - What training set measure is the best predictor of test set accuracy?

I'm running a random forest model on a training sample in R in order to make predictions on a hidden test set. I'm having difficulty in understanding how I should go about improving my model in order ...
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27 views

Choosing the parameters for an artificial neural network for time-series regression in R

I'm trying to build an artificial neural network (ANN) using the R "neuralnet" package, to predict streamflow from snow albedo (reflectance of the snow; controls the amount of heat absorbed by the ...
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19 views

k-fold on dataset

I have been doing a specific check of k-fold technique to see the difference using different number of folds and the corresponding result on the score obtained. To perform this test I have made ...
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18 views

full conditional posteriors for bayesian lasso

I am reading the original Bayesian Lasso paper, and its follow up; They look straightforward to implement, mainly because of the conditional posterior probability for the gibbs sampler; however, I ...
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1answer
31 views

Finding covariance matrix for weight priors for bayesian regression with feature space mapping of inputs

I want to implement Bayesian regression which returns the MAP estimate for given aggregation of columns of design matrix mapped into the feature space $\Phi(X)$, responses as a column matrix $y$ ...
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2answers
23 views

What differentiates one feature map from another in CNN

I understand in a convolution neural net that you may have several feature maps in the same layer, for instance one map detects curly loops for some letter and another detects straight lines. Here my ...
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30 views

How to find similar documents in a big data set

I have many text text documents and my goal is to find similar documents. Apparently it is a clustering type of question and LDA (Latent Dirichlet Allocation) is a good candidate to do that. However ...
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17 views

Alternatives to Google Prediction API?

The Google Prediction API seems like a great machine learning product because it is generic (works with any type of machine learning problem), and is very easy to use with a simple API. Unfortunately, ...
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1answer
19 views

multi-class logistic regression for ordered labels

I have a set of labells: A - no lesion B - mild C - severe If an instance from a class predicted as its nearest class not a big problem ...
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21 views

How is the mean area under the curve calculated?

I am using 10-fold cross-validation for performance estimation. From each of the ten iterations, I get an area under the curve (AUC) metric, e.g. ...
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67 views

Mathematics required for data scientist? [duplicate]

To read a book like Elements of Statistical Learning what are the mathematical prerequisites. I currently know Linear Algebra ( basic course ) , single variable and multiple variable calculus. I want ...
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29 views

How is the chance-level confusion matrix calculated?

I applied an ML technique on my dataset, and got this confusion matrix: 0 1 0 162 62 1 27 50 Funnily, the overall accuracy is worse than ...
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1answer
41 views

How to rank monthly data, using both trends and averages

I have a very large data set containing the daily searches for some Wikipedia entries. I am using the number of searches as proxy of popularity and want to rank the entries. Lets say I have entities ...
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2answers
41 views

Is parametric equivalent to linear?

Some supervised learning techniques, such as GLM (e.g., logistic regression), are linear and parametric. On the other hand, one of the claimed advantages of nonparametric supervised learning ...
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57 views
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May I use the whole dataset to prove the existence of a confounding variable in a machine learning framework if I don't use the labels?

I have a certain dataset that I am analyzing with machine learning techniques. I believe there is a certain variable (not used for training or testing the classifiers but is still known) that has an ...
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3 views

What are good tutorial on Weighted Finite Automata?

I would especially appreciate papers, books or tutorials with source code already available. Currently I'm reading "Spectral Learning Techniques for Weighted Automata, Transducers, and Grammars" by ...
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16 views

clustering 1d data with a competitive learning method [closed]

I have a 1D data, and I want to cluster that with any data using competitive learning method. How can I manage this? Thanks,
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10 views

Strange spikes in cost function during full-batch gradient descent

I was wondering what can cause spikes in the cost function (during training) similar to this one in the plot below: I am using a full-batch gradient descent, so as far as I know, with proper ...
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38 views

Best ways to model 'big data' given limited computing resources

Suppose I have a large data set(10 GB), with a response variable and multiple independent variables. What is the best way to utilize the data to build a model on? If the full data set includes 10 ...
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2answers
41 views

statistical prediction [closed]

I am new to statistical methods so this question may be very simple for you. I want to know some "statistical prediction methods" for a sequence of numbers. The numbers may represent financial or ...
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1answer
32 views

Prediction uncertainty intervals for predictions of machine learning algorithms

Assume I have a regression problem. I fit models on a train data set and tune their hyperparameters using CV. I then run the models on the test set. What is the best way to calculate prediction ...
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1answer
20 views

out-of-bag error estimate for Boosted Trees

In Random Forest, each tree is grown in parallel on a unique boostrap sample of the data. Because each boostrap sample is expected to contain about 63% of unique observations, this lefts roughly 37% ...
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26 views

Batch Gradient Descent - Parallelization

Here is the scenario that I have been thinking for sometime: You have a large dataset over which you want to run a regression analysis, using the classic gradient descent method to minimize the error ...
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19 views

how to improve linear regression model [closed]

i am working on a simple linear regression model for practicing in order to learn machine learning . my model runs correctly however it get a bad score which means it is a bad model so any advice for ...
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1answer
41 views

Feature engineering

I recently realized, that feature engineering (designing input vectors for machine-learning algorithm) is one of the most complicated tasks when applying known algorithms (for example kernel ...
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32 views

Adding observations by aggregating existing data

Question I'm aware that generating features from existing data can be a valid method for adding new features for a regression/ML algorithm*, but can you add observations generated from existing data? ...