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

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Feature that is numeric if true, or single value if false

In regards to feature engineering for machine learning models. I would like to engineer a feature that encodes the following: value can be true and if so it will measure a numeric (maybe ...
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20 views

What are the key steps in solving Machine Learning Problem

I am trying to make a summary to myself, what are the key steps for solving a Machine Learning problem. I tried to read good books, talked with peer, discussed many issues here, checked many web based ...
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Gaussian Process: How to use GPML toolbox for multi-dimensional input?

I am using MATLAB 2014_a student version I have 198 x 9 training data x (X1,X2,...,X9) and 198 x 1 target data y For now, I got linear equation among training data and target data ,for example, ...
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5 views

How can get F-measure, precision and re call and also Cluster labels in R

I am new to R. I want to use hierarchical clustering of R to cluster following distance matrix. ...
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23 views

How would you modify your model according to that confusion matrix?

How would you proceed with your model, if the confusion matrix looks like on the picture below? Classes 2, 3 and 4 get misclassified a lot among each other. EDIT: The Confusion Matrix was created ...
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5 views

Why my Convolutional Neural Network always produces the same outputs?

I used MatConvNet to build a CNN model for regression. The input size is 20×20×1×32, the output size is 4×1×32, the convolutional filter size is 3×3×1. Now I found after training the training error ...
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10 views

Correct definition of classes in classification tasks

I have to predict the values of a continuous target variable $Y$ using a bunch of $X$ features. Unfortunately, the regression approach does not provide satisfying results. Thus, I was thinking to ...
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11 views

Is cross entropy only applied on the last layer of an ANN?

I was reading about L1 regularization and from what I understand, we compute the cost of the last layer like: $\ w_{new} = w−\eta\frac{\partial C_{0}}{∂w}−\frac{\eta\lambda}{n}w $ However when using ...
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7 views

Compute all paths in graph that has multiple inputs and one output

I want to compute all the paths in directed acyclic graph from multiple inputs (x1, .., xn) to one output. The graph has the same depth which d and the inputs come to the graph at the same time (the ...
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6 views

Can Naive Bayes be used with feature hashing and one hot encoding?

I was wondering if a naive bayes implementation can be used with data that has been feature hashes and one hot encoded. The data I am looking at is mobile ad click data from the avazu kaggle ...
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22 views

Classify streaming, partially complete data into groups defined by prior clustering

Suppose I have M observation vectors, offline, $y_t$, $ t =1 ... M$, and each observation is $n$ dimensional. I then cluster these observations into $k$ clusters. For computing the clustering ...
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15 views

SVM - high number of support vectors leads to a high variance SVM?

I've tuned a SVM with radial kernel that has training error about 10%, but test error is about 38%, which surprise me. I tried to understand what may cause this and noticed the number of support ...
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Merging observations in Gaussian Process

I am using Gaussian process (GP) for regression. In my problem it is quite common for two or more data points $\vec{x}^{(1)},\vec{x}^{(2)},\ldots$ to be close to each other, relatively to the length ...
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3answers
41 views

A good description of the random forests method

Can anyone suggest a good book or article describing the random forests method of classification? I'm not satisfied with the way the subject is treated in "An Introduction to Statistical Learning with ...
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1answer
19 views

Heteroscedasticity in machine learning predictions

I am using a machine learning method (PLS) to predict a continuous variable, which currently does a pretty good job, with reasonable RMSE etc. However, the residuals exhibit heteroscedasticity, where ...
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1answer
10 views

Prediction for non-negative data using PLS/alternative

I am currently using PLS (the set of predictors are quite highly-dimensional) to predict a particular variable, $age$, and I am using Caret's train implementation using the pls method: ...
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5 views

How ksvd algorithm is considered generalized kmean?

I am trying to understand more details of this paper "KSVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation" proposed a new algorithm called Ksvd and claims it's a ...
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391 views

What are some good datasets to learn basic machine learning algorithms and why?

I am new to machine learning and looking for some datasets through which i can compare and contrasts the differences between different machine learning algorithms (Decision Trees, Boosting, SVM and ...
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10 views

Data complexity measure which affect classifier performance

As we strive to explain accuracy of machine learning algorithms, many authors suggest to start by degree of complexity in data. I am working in data complexity measure like: class ...
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1answer
17 views

Advice on a model or approach to layered dataset

I am attempting to develop a model to estimate the number of people in a space based on the Wi-Fi Traffic. At present, I have a dataset (in xml) which is structured like the following: ...
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13 views

Improving my knn prediction

I am still somewhat new to R and machine learning. I am trying to predict the cases of diabetes in the PimaIndiansDiabetes data set. My results were not the best- and I am wondering what I could do to ...
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13 views

Problem on Clustering Discrete Input using GMM

I want to do clustering using Gaussian Mixture modeling (GMM) on a set of data which is a 5-dimension vector of real values $(x_1,x_2,x_3,x_4,x_5)$. However the clustering result were pretty bad, ...
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1answer
22 views

Bias inputs in an RNN

As far as I'm aware, the bias inputs for a feed forward neural network are typically connected as follows: How are they connected in a recurrent neural network? (My guess is below)
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2answers
83 views

X-means algorithm and BIC

I want to simulate X-means algorithm based on [1] in MATLAB. I have some questions about this algorithm. X-means Algorithm Steps: (1) Initialize K = Kmin. (2) Run K-means algorithm. (3) FOR k = ...
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15 views

What neural network architecture and weights can approximate the following functions?

I learned how to represent all the boolean functions such as AND, OR, XOR etc. If a multilayer (recurrent) neural network can approximate any function arbitrarily close, what kind of architecture and ...
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1answer
17 views

Flag Random or Nonsensical Entries in a data set using R

This is a variation on my question Machine learning to catch fraud I have a data set with about 5 million rows The data set contains names and addresses of companies The name of the company is free ...
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1answer
17 views

what is “Minimum Length Least Square”

I am in the process of implementing Bayesian Lasso with Normal-Gamma prior; In section 3.3 mention The prior for the scale parameter $\gamma$ conditional on $\lambda$ is given by $v_\beta = 2 \lambda ...
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2answers
42 views

cross-validation: what is the standard deviation if the same value is obtained for each fold?

Here is a detailed imaginary example: I am using 5-fold cross-validation to estimate the generalization MSE of my predictive model. When I hold-out fold number 1, which contains 10 observations, say ...
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23 views

Cost function spiking upon using dropout on neural network

Upon using the dropout technique, my cost function is spiking arbitrarily. Is this normal? If not, how do I avoid it? I'm using a salt-and-pepper mask to drop out neurons at a dropout rate of 5%. ...
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1answer
28 views

Lagrangian multiplier: role of the constraint sign

I am beginner learning Lagrange multipliers with wiki article. Consider: maximize $f(x,y)$ subject to $g(x,y) = 0$ I understand that to maximize I must follow the gradient $\nabla {_{x, y}}^{}f$. I ...
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22 views

How do I use MatLab or R data model in an machine learning application [on hold]

I want to use matlab or R to create a prediction model, once this is complete how would I use that model in a an application?
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1answer
38 views

Classification problem where one attribute is a vector

Hello I am a layman trying to analyze game data from League of Legends, specifically looking at predicting the win rate for a given champion given an item build. Outline A player can own up to 6 ...
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19 views

Is there a classification model with possibility to set transition probabilities for each sample?

There are models where we can to set initial transition probabilities between classes like Markov models. But what if we need to change the probabilities dynamically depends on all previous ...
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1answer
6 views

Suggest suitable time series like ML model

We have data (1901 to 2002) in this schema: Fotrnight, Temp, Precipitation, WetDayFreq, (and other env variables), Cholera_cases we have one such table for each ...
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1answer
18 views

Preprocessing via PCA in Caret, then fitting PLS

I am dealing with quite highly-dimensional data, and am using (in R) Caret's preprocessing 'pca' method to reduce the dimensionality. However, dependent on the number of components I choose, I seem to ...
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1answer
22 views

Composite similarity of GitHub projects

As a hobby, I'm building recommendation system which finds related projects on GitHub. I'm computing Jaccard index for each repository, based on users who gave stars: $$J(A, B) = \frac{ \left\vert ...
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22 views

Why is my simple implementation of sub-gradient descent for SVM not converging?

As an exercise in understanding the mechanics of the Support Vector Machine, I am attempting to implement the SVM myself, in Python. I'm more concerned with understanding than efficiency, so I wish to ...
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1answer
31 views

Sampling : Gradient Boosting Tree

I have a question regarding the algorithm of Gradient Boosting Tree. I understand Simple tree is built for only a randomly selected sub sample of the full data set (random without replacement). Each ...
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1answer
31 views

What is the difference between kalman filter and extended kalman filter?

I am working SLAM based problems in robotics and I want to know whether I can use Kalman filter instead of the Extended kalman filter that is predominantly used ? If not, what is the difference?
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11 views

Multiple Response Regression in Spark MLLib

I am trying to do a regression using RandomForests in Spark ML where I have several input variables and would like to predict several responses. Training data would look like X = ...
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6 views

Equivalent method to simplex algorithm in machine learning

I always use simplex algorithm for minimization problems. Is there an equivalent approach in machine learning that could possibly be better, smarter?
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13 views

Multi-tier classification

First of all, I'm not sure wether the question title is correct, but I'm facing a puzzling problem. Please point me to the correct term and some relevant literature. This is the problem: Let's say I ...
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23 views

sentiment analysis using convolutional neural networks

I was trying to modify YoonKim's code for sentiment analysis using CNN's. He applies three filters of heights=[3,4,5] and ...
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4answers
809 views

Why splitting the data into the training and testing set is not enough

I know that in order to access the performance of the classifier I have to split the data into training/test set. But reading this: When evaluating different settings (“hyperparameters”) for ...
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52 views

Comprehensive list of misnomers in machine learning

Are there any reference document(s) that give a comprehensive list of misnomers in machine learning? I would like to have a list and simple explanation if needs be that I could go through easily (vs. ...
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14 views

Predicting lat/long from binary features

I have a number of observations that occur around my city (a small area), and several of them have latitude and longitude. I have been looking into predicting the latitude/longitude of the ...
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10 views

Non linear dimension reduction method that provide a way to map data from embedded space to original data space

I am looking for dimension reduction tools that allow to map data from the low dimensionnal embedded space to the high dimensionnal space of the original data. For example, Gaussian process latent ...
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34 views

Boosting: why is the learning rate considered a regularization parameter?

I understand that the learning rate parameter ($\nu \in [0,1]$) in Gradient Boosting shrinks the contribution of each new base model -typically small trees- that is added in the series. It was shown ...
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What algorithm to use in order to find pairs of numbers belonging to one person? [closed]

There are data. In each row: Lac---ID of the mobile stations' group cid --- station' ID within LAC msisdn--phone number imei--device number. Based on the first 8 numbers: ...
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28 views

How to interpret prediction accuracy based on error analysis in test and validation sets?

I would like to calculate accuracy of my prediction model based on polynomial regression and I got some values for the test and validation errors 3.895 and 4.0125. I am wondering how these values for ...