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

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Scikit Random forest prediction probability gives rounded off values

I am using random forest in scikit learn for classification and for getting the class probabilities , I used pred_proba function. But strangely it outputs probabilities rounded to first decimal place ...
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2answers
26 views

Name some techniques similar to Random Forests

I'm interested in what techniques are out there that are similar to, but not the same as, Random Forests. Either for classification or regression or both. Particularly interested in techniques which ...
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37 views

Fitting a trading model

I have a high frequency time series of the bid and ask prices of a stock recorded on every tick. For each data point I also have a certain indicators that predict the future movement of the price. The ...
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1answer
33 views

Weight shrinking in linear regression by L2 regularization

Quoting Prof. Bengio from his Deep Learning text (http://www.iro.umontreal.ca/~bengioy/dlbook/regularization.html), $ w = (X^{T}X + \alpha I)^{-1}X^{T}y $ We can see L2 regularization causes ...
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5 views

Reduce the FP rate for a Random Forest (sklearn)

I am working with the scikit-learn random forest classifier and I want to reduce the FP rate by increasing the number of trees needed for a successful vote from greater than 50% to say 75%, after ...
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7 views

How to model the problem of predicting failure in Server Clusters

The problem goes as follows - There is a cluster of Servers. Whenever there is failure/anomaly in any of the server, a report is logged. Some of the features of the log report are Time of Failure ...
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7 views

Website classification using metadata features

I want to fit a model that predicts a website type according to metadata features that I manually collected, such as - Average text length, average # of pics, average outgoing links per page, etc... ...
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18 views

Getting an error message “Error in if(reached.threshold < min.reached.threshold)…” while training network using neuralnet package

I'm using R to create train and test a neural network on a time series (the annual sales of a company over a large period of time). As using the package's default learning algorithm (resilient ...
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3answers
387 views

What can we learn about the human brain from artificial neural networks?

I know my question/title is not very specific, so I will try to clearify it: Artificial neural networks have relatively strict designs. Of course, generally, they are influenced by biology and try to ...
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1answer
71 views

Why is SVM better for bioinformatics analysis?

I have used five different algorithms: bagging, boosting, C4.5, random forests and SVM, for binary classification of biological data relating to peptide sequence. The dataset comprised of ...
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2answers
31 views

what is the difference between area under roc and weighted area under roc?

Thanks in advance for the help. I have an unbalanced dataset that I am using for a binary classification problem. The classes are unbalanced. I believe that in such a case that weighted area under ...
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13 views

how to understand this neighborhood components analysis model?

I am reading an article with title "neighborhood components analysis" lately. http://papers.nips.cc/paper/2566-neighbourhood-components-analysis.pdf. This article is trying to introduce a linear ...
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1answer
40 views

How to use linear regression for heavily skewed purchase data?

I am trying to use multiple linear regression to predict the amount that a particular user will spend in a particular time frame on a particular site. Part of the problem is that there are very few ...
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1answer
32 views

In a Boltzmann machine, why isn't there a simple expression for the optimal edge weights in terms of correlations between variables?

Suppose I have a fully connected, fully visible Boltzmann machine (no hidden variables) with binary variables $x_i\in \{+1, -1\}$ that defines the probability distribution $$ p(\mathbf{x} ; ...
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10 views

when to stop this convex optimizations algorithm?

I am reading the article with title "metric learning with collaping classes" lately http://papers.nips.cc/paper/2947-metric-learning-by-collapsing-classes.pdf. See this thread (what is 1/0 in this ...
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18 views

Active acquiring as a special case of active learning

I explore an approach for collecting data. This approach is similar to active learning, but there are few differences. The focus of the approach is on collecting training data (labeled data) ...
2
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1answer
42 views

train an SVM via back propagation?

I was wondering if it was possible to train an SVM (say a linear one, to make things easy) using back propagation? Currently, I'm at a road block, because I can only think about writing the ...
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3answers
57 views

Use Edge detection in Image classification

I am having five types of objects (flower, building, face, pair of shoes and a car) in my object recognition and i need to classify these. Identifying through edges in this type of data set seems to ...
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4answers
817 views

Why is Logistic Regression called a Machine Learning algorithm?

If I understood correctly, in a Machine Learning algorithm, the model has to learn from its experience, i.e when the model gives the wrong prediction for the new cases, it must adapt to the new ...
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1answer
37 views

What does “node size” refer to in the Random Forest?

I do not understand exactly what is meant by node size. I know what a decision node is, but not what node size is.
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1answer
46 views

Anomaly detection in time series data

Hi I have a large data set of objects, each containing a list of the same attributes. The data is arranged in a time series so that the value for an attribute for an object is indexed by its time. I ...
3
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1answer
14 views

nested cross-validation

if my outer cv is 5-fold, after the process, i have 5 final models, then apply these 5 final models from each CV to the whole dataset (training+validation+testing). For my case, the final 5 accuracy ...
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1answer
27 views

Using Fisher LDA in R

I have run a large study looking at traumatic brain injury in patients I have conducted CT scans on patients very soon after the injury as well as neurocognitive testing and then repeated this at 1 ...
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1answer
33 views

Can I Interpret the impact of variables like positive or negative on the model by Random Forest, as I can do by Logistic Regression

I have created a model for prediction of candidates presence or not . I have used Logistic Regression and Random Forest . By Logistic Regression, I got coefficients associated with 100 features and I ...
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1answer
27 views

Independence of data points assumption

While reading an ML book, I realized that most of the time, the input data points are correlated with each other, and hence their observation is not independent. But then, why do we assume that the ...
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R | NA/NaN/Inf in foreign function call | e1071 SVM [migrated]

Dataset: https://archive.ics.uci.edu/ml/datasets/Chess+%28King-Rook+vs.+King-Pawn%29 Code: ...
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18 views

Conclusion from PCA of dataset

I have a set of data for sequence labeling. I did PCA with (with 2 principal components on the x and y axis) on the dataset and it turns out as below: Using an LSTM network to classify the dataset ...
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37 views

How are radial basis functions (RBFs) networks extended to use multiple layers?

I am trying to understand the interpretation of radial basis functions (RBFs) as networks and then trying to understand the relationship it has to "normal" neural networks and how to extend them to ...
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2answers
111 views

Can a neural network learn a functional, and its functional derivative?

I understand that neural networks (NNs) can be considered universal approximators to both functions and their derivatives, under certain assumptions (on both the network and the function to ...
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1answer
45 views

What is the right algorithm to detect segmentations of a line chart?

To be concrete, given 2D numerical data as is shown as line plots below. There are peaks on a background average movement (with small vibrations). We want to find the values of pairs (x1, x2) if those ...
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0answers
31 views

How is prior knowledge of letter/word patterns incorporated into handwriting (or speech) recognition?

Using handwriting recognition as an example, we can train various models to recognise individual characters but to actually be useful we must incorporate prior knowledge of common character sequences, ...
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0answers
53 views

what is 1/0 in this article?

I am reading the article with title "metric learning by collapsing classes" lately http://papers.nips.cc/paper/2947-metric-learning-by-collapsing-classes.pdf . Everything goes well until the equation ...
2
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1answer
33 views

How does one do Stochastic Gradient Descent (SGD) on an objective function that has a regularizer?

I know that for Stochastic Gradient Descent, one picks a data point $(x_n, y_n)$ at random from the training set $S_N$ and then updates the parameter of the model in question. If the cost function ...
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7 views

Bigdata cluster compatible distributed predictive model [migrated]

I might be asking a dumb question but my question is can I write a python program (lets say a classifier) using some library that scales in hadoop (not only using a simple parallel processing).The ...
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1answer
75 views

What algorithm can I use to find correlations between events?

I am new to machine learning so I am trying to find some literature but I'm not even sure what to Google for. My data is of the following form: ...
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1answer
28 views

sampling distribution of the mean for arbitrary 1-D pdf

I want to compute the sampling distribution of the mean for $k$ samples from an arbitrary, known probability density $f(x)$, with $x \in \mathbb{R}$. What is the most efficient way to do so ...
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1answer
27 views

what is the relation between “data visualization” and “embedding”? [closed]

I am reading several articles about metric learning lately. Sentences like "build better data visualizations via embedding" and "low-dimensional linear embedding of labeled data" pop up very oftenly. ...
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0answers
18 views

Feature selection + classification in Caret

I'm using Caret to apply a bunch of different machine learning algorithms for phenotype prediction from gene expression data. With about 20,000 genes, I'd like to perform filter feature selection ...
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13 views

How to obtain Matthews correlation coefficient in Rocr? [closed]

I am trying the following example: ...
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49 views

Why do we have to be concerned about the problem of overfitting on the training set?

For a hypothesis set $H=\{h_1,...,h_M\}$, randomly sampled training set $D_{train}$, and a learned hypothesis $g$ using $D_{train}$, the VC-bound of a finite hypothesis set tells us $$ ...
3
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1answer
39 views

How do gradients propagate in an unrolled recurrent neural network?

I'm trying to understand how rnn's can be used to predict sequences by working through a simple example. Here is my simple network, consisting of one input, one hidden neuron, and one output: The ...
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2answers
64 views

Is it right to consider the output of the neural network as its confidence in predicting the output?

Suppose I have a single output sigmoid (tanh) that is producing an output ranging [-1, +1]. Is it right to consider this output as its confidence measue of predicting the output. The output value ...
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1answer
31 views

Real time example: Estimation for incomplete data

Following is from Csiszar and Shields' FnT monograph "Information Theory and Statistics": The expectation–maximization or EM algorithm is an iterative method frequently used in statistics to ...
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1answer
27 views

How can I do a one vs all classification (binary classifier) with a neural network

I have a set of images that belong to a particular class. Then, I have another set of images that do not contain any image of the above particular class. So, effectively I have two sets of images ...
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8 views

Suitable classifier for 'objects on a string' data [on hold]

I don't know if this can be considered a subjective question, but I have no option but to ask someone. My problem: I have a series of strings (or lines, think metal strings, not text strings) on ...
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1answer
34 views

Predicting Co-Ordinate Data

This is on a prediction model we were trying out among a bunch of us trying out ML for the first time. Basically I have a training data set of network user ID's with their location (latitude and ...
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0answers
37 views

Understanding convolution [closed]

I'm reading about convolutional neural networks. Are there different feature maps that use different matrices or different calculations? How can one calculate different feature maps from an ...
0
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1answer
40 views

Can one derive Radial Basis Functions (RBFs) with movable centers from Tikhonov regularization?

It is well know that the "usual" Radial Basis Function can be derived from Regularization that imposes small derivates. More precisely it is well known that the following: $$ f(x) = \sum^{N}_{n=1} ...
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Negative quadratic data-fit term of marginal likelihood in Gaussian process regression

I am trying to implement an auto-tuner for hyperparameters of a Gaussian process regression. A way of doing this is optimizing the marginal likelihood function. The marginal likelihood contains the ...
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0answers
10 views

Choosing keypoints for a training set and their prospective number

I am building a software to classify cells from images taken by a microscope. I have a dataset of images of cells to use as training dataset - I have extracted Keypoints from each image using ORB - ...