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

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Are all generative Models based on Bayes?

Reading about deep learning I encounter various different kinds of hierarchical networks, many of which are generative. 1) Are all of the generative networks based on Bayes? 2) If not, how do they ...
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How to return output values from MLP? [on hold]

I developed my MLP with two outputs. I used Neuroph Studio. I then imported it in NetBeans using the follwoing code ...
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I am learning advanced machine learning and would to build a machine learning library in python.Please help(For learning purposes only) [on hold]

Need some resources like books,blogs etc. Like something on the lines of scikit learn.I just want build an ml lib to dig deeper into ml.Not trying "reinvent the wheel" Background about me:Have read ...
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14 views

Neural networks that can reach state-of-the-art accuracy with two or three hours training?

Are there some neural networks that can reach state-of-the-art accuracy with two or three hours training, on dataset like CIFAR, MNIST,etc...
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12 views

Comparing and evaluating win probabilities in sports from different settings

Background I'm trying to predict the probability that the home teams wins a certain sports game, for each minute of the game. Taking these win probabilities together produces a nice visual of the ...
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1answer
12 views

Applying filters learned from convolutional neural networks

I have a neural network that I trained on 32 * 32 px size images. Can I use these filters learned from the network on larger images not used in training the network such as a 600 * 800 px image? Or ...
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3 views

finding and comparing temporal and location-specific pass patterns in a soccer game

I have data on several soccer matches, where ball passes have been recorded in terms of XY-location where the pass starts, XY location where the pass ends, the team making the pass, the player making ...
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1answer
29 views

true negative is 0% whereas true positive is 100% correctly classified

I used Naive Bayes from Spark's MlLib to train a model and test it on the data (in the form of an RDD). The results were confusing. the data and results are as follows: The problem is a binary ...
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1answer
15 views

Convolutional Neural Network for 3D point cloud?

Can Convolutional Neural Networks or Deep Architectures be used for generating 3D point clouds ?
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Recurrent Neural Network (RNN) topology: why always fully-connected?

I've started reading about Recurrent Neural Networks (RNNs) and Long Short Term Memory (LSTM) ...(...oh, not enough rep points here to list references...) One thing I don't get: It always seems that ...
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12 views

choosing prior parameters for variational mixture of Gaussians

I am implementing a vanilla variational mixture of multivariate Gaussians, as per Chapter 10 of Pattern Recognition and Machine Learning (Bishop, 2007). The Bayesian approach requires to specify ...
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1answer
51 views

Is it reasonable to study neural networks without mathematical education?

Given the modern state of machine learning technologies and tools (e.g. TensorFlow, Theano, etc.), it seems like entry threshold have recently lowered and it is enough to be able to program on, say, ...
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20 views

Predict revenue of click

I'm trying to build a model for eCommerce that will predict revenue of a click that comes via online-marketing channels (e.g. google shopping). Click goes directly to product detail page (so it's not ...
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10 views

Adversarial sequential learning with a linear model

I have a problem with the following characteristics: The value of an observation is a function of its predictors The nature of the relationship between value and predictors changes slowly over time ...
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13 views

Simple Bayesian Classifier for spam detection

I am a very beginner at machine learning, and I'm reading a book about it. I came across some lines of code in R for naive bayesian classification for spam detection. This is the code: ...
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19 views

tensorflow: How to feed numpy.ndarray? [on hold]

I hope this is the right community to ask in. I decoded a JPEG image and have it in the shape n_samples x n_features as a two-dimensional numpy.ndarray. I feed this to tensorflow as following: ...
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1answer
26 views

Mixture Density Network: What is C?

I'm currently trying to implement a Mixture Density Network (MDN) based off of the original paper here. Most of the equations seem pretty straight forward but on page 6 (7 of the PDF) equation 23 has ...
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5 views

how to choose parameters for paralysis of neural network classificator?

I have multilayer feedforward neural network and I learn it to do multi classification using back propagation method. Can you provide an example of how to create paralysis of neural network (when nn ...
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5 views

svm audio classification [on hold]

I am working in project for classifing a human voice with SVM and it is based on the MFCC coefficient. I have the program in matlab to calculate MFCC, it gives 12 vector of MFCC. and I have the ...
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16 views

How is the 'tau' variable calculated in locally weighted linear regression? [on hold]

I was wondering how the tau variable is calculated in locally weighted linear regression. Is it determined by humans, or is there an algorithm to determine its ...
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1answer
75 views

Computation of the marginal likelihood from MCMC samples

This is a recurring question (see this post, this post and this post), but I have a different spin. Suppose I have a bunch of samples from a generic MCMC sampler. For each sample $\theta$, I know the ...
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13 views

Variational Autoencoder for feature extraction

I would like to ask if would it be possible (rather if it can make any sense) to use a variational autoencoder Auto-Encoding Variational Bayes for feature extraction. I ask because for the encoding ...
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9 views

How to classify group of events (or actions) from an event log

Given data that contains events carried by group members (e.g., in the format of 'group_id, member_id, event_id, timestamp'), and label for such history data mapping a sequence of group interaction ...
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30 views

Repeated training examples in Gradient Descent

I am new to machine learning and trying to understand stochastic gradient descent. I understand in stochastic gradient descent, in each epoch, randomly an example is picked and given to the model. So ...
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1answer
26 views

Why are gradient boosting regression trees good candidates for ranking problems?

I have been reading up on gradient boosting machines, and in particular GBRT's. I've come across numerous mentions (and finally tracked down some papers) on applying these models to ranking problems - ...
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25 views

Can a model recognize the interactions between variables?

I have a data set similar to the following one, ...
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handwritten hindi numeral recognition using SVM

I have used LIBSVM to classify the hindi handwritten numerals . I have got a result of 93.38 % , when I used C=500 and Gamma = .004. I would like to get an idea about k fold cross validation and the ...
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converting feature from string to categorical reduces classification accuracy

I am working on San Francisco crime classification problem from kaggle. https://www.kaggle.com/c/sf-crime during the work I encountered something unexpected. I applied scikit learn's random forest ...
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6 views

Find a maximum value for input data

I have a set of 20x20000 input variables and 1x20000 target values. I want to find a best combination of 5 variables out of 20 on a condition that other 15 variables are constant to get the best ...
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14 views

Method to determine whether or not users had a bad experience based on multiple variables: Average Bandwidth, Latency, and frame rate

I would like a recommendation on the best statistical method to use, as well as any suggested R packages to achieve this goal. I have three variables, Bandwidth, Latency, and frame rate for a set of ...
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3 views

forward wrapper feature selection method on python [migrated]

I've coded a decision tree for my dataset. I'm using the semeion.data which is found at https://archive.ics.uci.edu/ml/datasets/Semeion+Handwritten+Digit. Now I need to find out how to use ...
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18 views

Can supervised machine learning techniques infer the formula (if it exists) for a statistical model?

Suppose that we have response data $y_i$ generated by a specific mathematical function $y_i=\mathcal{F}(X_i)+e_i$ where $X_i$ is a vector of predictor variables with random error term $e_i$. Without ...
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1answer
44 views

Bayesian treatment of outliers

In a supervised learning problem, I have a training dataset $D$ comprised of samples $x$ and their corresponding labels $\omega$. From this data, I attempt to learn the true distributions ...
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1answer
19 views

The unique variance in Factor analysis

This might be a rather simple question, but this is troubling me a lot? Please help. Suppose in a factor analysis model, there are three variables $x_1$, $x_2$ and $x_3$, and two latent factors ...
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1answer
7 views

Handling missing/rare levels in predictor in data samples

Let us assume we have a dataset with one catigorical variable, which is represented in R as a factor. I am performing crossvalidation to assess models, for which I need to perform stratified sampling ...
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1answer
29 views

Random Forest model good train and test performance but bad “real world” performance

I am working on a classification problem where I need to classify objects based on a visual data. There are a couple hundred different classifications to be made and I have around a million plus ...
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30 views

How to know the importance of all the variables and levels in them using Random Uniform Forest in R?

I have a dataset containing 3 parameters (Region( factors - say US,UK,Aus,NZ),Domain or Industry( factors - say IT,Electrical,Mechanical) and Scope - good or bad). Using Random Uniform Forest package ...
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9 views

Classification of overlapping hetegenerous cell nuclei

We are two people doing a image analysis project on segmentation of cell nuclei. Our data set consist of about 300-400 cell nuclei, from 10-15 images containing different cell types. Our main problem ...
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How to deal with heterogeneous data set

Problem I have a dataset that contains three types of objects: simple objects, object groups and meta-groups. Meta-groups contain simple objects and groups. Each simple object correspond to an ...
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7 views

Sample for Algorithm Implementation [on hold]

How can a 10 * 10 matrix, with 10 columns co-related with each other with some statistical functions and 10 rows as a time-series instances be sampled as a single instance ? I would like to plot N ...
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16 views

Best approach for calculating confidence score (p-value) - for Bayes models

This is a generic question on the best approach for giving a p-value to a "most likely" solution given by a graphical Bayes model. I am building a graphical model in Stan, for finding the most likely ...
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27 views

Defining Groups of 1D Data In a Time Series

I'm trying to analyze the following data. I have a large collection of time collections, and for each time collection, I want to figure out groups of times that are between longer groups. Imagine ...
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1answer
19 views

Can feature with high positive correlation have opposite weights sign? [duplicate]

I have two features for a binary classification problem which are highly positively correlated. (0.79) But when I build a logistic regression classification then I see their weights are opposite in ...
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21 views

Scaling overlapping subsets, optimizing nearness [on hold]

For a set of two thousand xyz points, I am multiply-scaling the z values. The points exist in overlapping subsets. Each subset is scaled by a float variable. In all there are anywhere from ...
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1answer
25 views

How and what do I train in my Convolutional Neural Network [on hold]

I have been trying to research and implement a convolution neural network in c++, and I think I understand the basic architecture of it. My problem is that I am incredibly confused as to what is ...
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20 views

Flexible prediction with neural network or other method

I want to use neural network for my first time, but I need to check if it fits for my case. So, my idea is to teach a model on data like Y = f(X1, X2...XN) and ...
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1answer
17 views

Large number of positive labels in classifier when actual population has few

I have been tasked to help with a sort of classifier. In the make up of the problem the set we want to identify as "Positive" is know to be very very small. However the training set I have been given ...
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1answer
27 views

deep learning in mobile apps [closed]

Can deep learning be applied in mobile apps, and if possible how? Is it possible ? to deep learning needs more computational cost? how can we minimize the computational cost for deep learning on ...
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39 views

What's an intuitive explanation for why MAP is variant under parameterization?

I understand why MAP is variant under parameterization mathematically, but I don't really understand it intuitively. To help me out, my professor gave me an example where reparameterizing MAP ...
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How does Weka chiSquaredAttributeEval generates single attribute selection list while Chi Square itself is class based?

I have implemented my own Chi-Square ranker in C# however the example i found on the internet shows that Chi-Square ranks the each attribute within its class However Weka generates attributes as a ...