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Questions tagged [machine-learning]

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

2
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0answers
22 views

what could cause these bizarre ML results?

I have a large set of images that I want to classify as "happy" or "sad". Each image is also tagged with the distance from the camera to the object being photographed, but for complex reasons, I'm ...
2
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0answers
14 views

How can I get RMSE from RMSLE [duplicate]

Is that correct If I take e^RMSLE will the resulting value give me RMSE or I am missing sometihing . I want to interpret RMSE from RMSLE
1
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0answers
7 views

ML Sampling question - Can I increase sample size of current dataset with older copies that have changed over time

I am working on a multinomial machine learning algorithm that labels stocks with buy/sell signals. My code updates with the most recent quantitative data about the stocks daily, so obviously the data ...
0
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0answers
8 views

forward sampling for Bayesian network with continuous variables and equation-based causal relationships

I have a physical system which can be represented by the following Bayesian network. It has the following characteristics 1) The encoded variables are continuous variables 2) The causal ...
1
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0answers
15 views

Is it possible to use q learning to achieve machine reading? [on hold]

I'm playing with ideas and wondering if it's possible to use q learning for machine reading and answering questions. I'm a beginner in AI even though I've programmed other things for many years, if ...
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0answers
21 views

how to model string pattern to character occurence in deep learning

In my question on stackoverflow, I was trying to decode concatenated string into partitions for example, ...
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0answers
13 views

Unsatisfactory prediction error - is it possible to improve accurancy? [duplicate]

I'm green in ML field and I try to classify user reports to valid/invalid. My dataset contains of Valid - 7355 samples Invalid - 6285 samples So, I devide data into train and test ...
0
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0answers
13 views

RStudio odbcConnectionExcel obsolete [on hold]

Error in odbcConnectExcel(filename, readOnly = FALSE) : odbcConnectExcel is only usable with 32-bit Windows Does anyone know the 64-bit version of the code?
6
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1answer
120 views

Variance of average of $n$ correlated random variables

Reading about deep leaning, I came across the following formula. $$ \mbox{var} \left( \frac{1}{n} \sum_{i=1}^{n} X_i \right) = \rho \sigma^2 + \frac{1-\rho}{n} \sigma^2 $$ where $X_1, \dots, X_n$ ...
1
vote
1answer
14 views

How to estimate the leafsize of the kd-tree?

The kd-tree implementation proposed by the scipy python libray asks for the value of the leafsize parameter that is to say the maximum number of points a node can hold. It is by default set to 10. ...
1
vote
1answer
20 views

Is a polynomial kernel ridge regression really equivalent to performing a linear regression on those expanded features?

Say we have a dataset, X, which is Nx2 where N is the number of examples and 2 is the number of dimensions "features". If we were to run a kernel ridge regression (or SVM or whatever) on these ...
2
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0answers
21 views

$L^2$ Regularization and Hessian Matrix [duplicate]

In the second paragraph it is mentioned that eigenvector of $H$ is rescaled by a factor of $\frac{\lambda_i} {\lambda_i +\alpha}$ What exactly meant by that ?
1
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0answers
26 views

Best approach for learning Reinforcement Learning coming from economics?

I have an economics background so I have have Calculus, Linear Algebra, Diff. Eq., 2 semesters of Stats and Prob. and some Python Knowledge. My school offers a 2 months postgraduate course in ...
0
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2answers
25 views

Meaning of Probability Distributions in RBMs

I'm new to machine learning, and am trying to understand some of the basics of Restricted Boltzmann Machines. Unfortunately, I don't have a background in statistics yet beyond a basic understanding, ...
1
vote
1answer
14 views

Understanding `score` in LightGMB

I'm newly introduced to the LightGBM for a regression problem. Having read the documentation of LightGBM (here), I got puzzled about the ...
0
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0answers
9 views

Replacement for angular distance metric

I am looking for a distance metric that could be used instead of cosine/angular distance for high dimensional data. Metric that is limited the same way as cosine/angular distance is would be great. ...
1
vote
1answer
63 views

Understanding Rejection sampling

In acceptance rejection sampling, what is the intuition behind using the formula for finding c( a constant that envelops the target density function): $$c\geq derivative\left(\frac{target\ ...
0
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0answers
10 views

Generalization and Over fitting

I am reading the book Deeplearning by Goodfellow. There it explains about three factors about generalization, which I find it quite blury to imagine. Excluded the true data generating process—...
0
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0answers
18 views

Feature Selection in high dimensional data [closed]

In my dataset I have 1000 rows and 5000 dimensions. What is a good approach to select important features out of such a high dimensional dataset before I start with the model building. I would prefer ...
1
vote
1answer
11 views

Presenting results of SVM model following LOOCV

I have a small dataset of 60 points and used an SVM regression model (with linear kernel) to train a model to predict $\bf{y}$ from two features, $\bf{x_{1}}$ and $\bf{x_{2}}$. I used LOOCV to provide ...
2
votes
1answer
22 views

How a stationary time series forecasts non-stationary values?

In time series data, non-stationary data is first made stationary (Using Differencing or any other methods). We train the model using this stationary data. So how come model's forecast will be close ...
0
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0answers
22 views

Fixup initialisation for residual networks

In their Fixup Initialization: Residual Learning Without Normalization, authors suggest: Fixup initialization (or: How to train a deep residual network without normalization) 1. Initialize the ...
0
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0answers
19 views

Calculating the true error comprised of two probability distributions

Let $X$ = {0,1,2,3,4} and $Y$ = {0,1}. A probability distribution $D$ defined on $X\times Y$ such that $D_x$ = Binomial(4, 0.5) and $D_{y\mid x}$ = Bernoulli(0.5). Given the predictor: $h(x)$ = $0$ ...
0
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0answers
13 views

Confidence interval for sum(observed) (continuous, right-skewed) divided by sum(expected) (continuous, right-skewed)

I need confidence intervals for an o/e metric based on a continuous variable (observed days/ expected days) sumed up for all the people in the population.
0
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0answers
9 views

What are the advantage of using Sigmoid and Softmax and disadvantageous of both? [duplicate]

I am trying to understand the architecture of the neural network. I am supposed to make decision of how many hidden layers and what activation functions to use in the hidden layer and which activation ...
1
vote
1answer
19 views

Mix of categorical and continuous data in neural network

Given a shallow or deep neural network, how would one go about using both continuous numerical input features and categorical features? For example, given a network that receives a set of 100 ...
0
votes
1answer
14 views

When the validation set is a subset of the training set

I am doing the following but I am not sure if this is right or which behavior should I expect: A union B union C is the full dataset Training set: is A union B datasets Testing set: is C Validation ...
-1
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0answers
11 views

How to reach streaming learning in Neural network?

As title, I know there're some model supporting streaming learning like classification model. And the model has function partial_fit() Now I'm studying regression ...
0
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0answers
20 views

compare the outputs of two different ML models

Let's imagine I have two completely different multi-class ML models, let's call them ML1 and ML2. The models were trained on completely different data with different target classes. As an output, the ...
0
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0answers
7 views

Model Training and test accuracy suddenly dropping for a Mulit Layer Perceptron from 98% to 9% (test)? [duplicate]

I was exploring the tensorflow library and was working on an MLP for the mnist dataset. It is 5 layers MLP trained for 10000 iterations on batches of 100. After training the model up to 9000 ...
1
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0answers
23 views

Dummy variables with dummyVars() - return to original columns [closed]

For building a machine learning model I used dummyVars() function to create the dummy variables for building a model. ...
2
votes
2answers
77 views
+50

Object Localisation without Classification

I have a data set of photos containing an object in each of them. I want to find out the coordinates of rectangle enclosing the object. Note that each photo contains exactly 1 object (for example, if ...
2
votes
0answers
22 views

How to Fine Tune a pre-trained network

I'm looking into using Transfer Learning to take the ResNet50 model trained on ImageNet and fine tune it to my own dataset using Keras. However, I feel I have some misconception about what exactly ...
1
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0answers
13 views

compute the KL divergence between two datasets

I have two datasets $D1$ and $D2$ in two different feature spaces $\mathcal{X}_{1} \in \Re^{m}$ and $\mathcal{X}_{2} \in \Re^{n}$. Further assume that the datasets have different number of data points....
1
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0answers
31 views

What if the best k in k-NN is equal to the number of data points?

I need to train a regressor (in the machine learning sense). I have tried many different methods and so far nothing works better than just a constant prediction. In other words in looked like I have ...
0
votes
1answer
24 views

Can you implement Replay Buffers for Reinforcement Learning when most experiences give zero reward?

Specifically, for a deep deterministic policy gradient, DDPG, to expedite the learning speed, it's recommended to use a Replay Buffer What if the reward is only given at a terminal state? Or, most of ...
2
votes
1answer
82 views

Define statistical potential energy [closed]

I am looking for a statistical method that closely relates to the idea of potential energy. Here is a quick google definition for potential energy "...the energy possessed by a body by virtue of ...
0
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0answers
8 views

Extracting regimes from a time series

Trying to find a good way to solve the following problem: I have daily time series $\{x_n\},$ say for the last 10 years. During that time span there are several shorter periods (say, Dec '12 - April '...
-1
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0answers
12 views

how to feed new test set and get result from deep learning model trained in gpu [closed]

i trained a code NN model using GPU exmachina torch framework, code downloaded from github and now need to feed new test set and get results
1
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0answers
15 views

Discussion on building logic for Churn for monthly renewal [closed]

I have a subscription based business dataset which looks like this: ...
1
vote
1answer
25 views

Removing noise with Variational Autoencoders

I have one question that is related to variational autoencoders: can they be used as a denosing algorithm in the same way as standard denosing autoencoders? I generally see people removing the ...
0
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0answers
17 views

temporal autocorrelation machine learning algorithms

I am trying find out the relationships of stream integrity against Land uses. I have 4-years of stream integrity data (1998-1999, 2004, 2009, 2014) and corresponding land use data of 1995, 2002, 2007, ...
0
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0answers
12 views

how to deal with dependent variables as a list of integers in machine learning

In my working project, I'm building machine learning models to predict number of hospital admissions from patient profile. The dependent variable, # of hospital admission are integers from 0 to 8. ...
0
votes
2answers
31 views

Evaluating Classifiers k fold CV or ROC

I've been doing a project to determine the 'best' classifier for classification on a dataset from UCI. I used 10 fold stratified cross validation to calculate the mean accuracy. However it was ...
1
vote
2answers
56 views

on-line regression with 1 output [closed]

I have 12 input variables from sensor (IMU) to predict 1 output (Speed of a boat) variable. Is it possible to use regression (or something else?) in this case where it is a continuous data stream from ...
1
vote
1answer
9 views

Good way to use word similarity as a feature in supervised ML on text

I have a pretty low N data set of small sentences tagged with a label. I would like to create a classifier on this dataset. The word choice is not very variable since the domain is pretty specific. ...
0
votes
0answers
5 views

Will merging class labels in pre-trained model hurt transfer learning?

I'm using a large image dataset labeled with 15 classes to train a ConvNet model. The resulting model will then be used to enable transfer learning in a tiny dataset labeled with only 3 classes. The 3 ...
0
votes
0answers
23 views

Which algorithm is suitable to predict playing xl [closed]

NOT SURE WHAT THE QUESTION TITLE SHOULD BE. SORRY ABOUT THAT. I am new to Machine Learning and I am a huge sports fan(soccer in particular). So I was wondering if I could apply some technique for ...
0
votes
0answers
18 views

Multivariate time series with a binary dependent variable

I am currently working on a multivariate time series data set with 1 dependent variable (y) and 60 independent variables ($x_1$,$x_2$,....$x_{60}$). The dependent variable is a binary variable (0 or 1)...
0
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0answers
8 views

Determine input array that approximates a target output array from complex numerical simulation?

I believe the following problem is ideally suited to a machine intelligence approach, but am unsure where to start. I've used scikit-learn previously with downloaded datasets, but the following seems ...