Stack Exchange Network

Stack Exchange network consists of 175 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.

Visit Stack Exchange

Questions tagged [machine-learning]

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

7
votes
0answers
509 views

document classification : what is the difference betwen fasttext and DANs ?

I came across two interesting papers which describe promising approaches for document classification using word embedding. [1] the first one is the fasttext algorithm described in the paper : Bag of ...
6
votes
0answers
49 views

Strategies for handling unlabeled data which is slightly different from the labeled data

Suppose you have a dataset with the following properties: The number of samples is fairly large (~100K samples) There are ~150 contextual features and 1 feature consisting of a text-string (which can,...
5
votes
0answers
515 views

Input for LSTM for financial time series directional prediction

I'm working on using an LSTM to predict the direction of the market for the next day. My question concerns the input for the LSTM. My data is a financial time series $x_1 \ldots x_t$ where each $x_i$...
5
votes
0answers
417 views

I am struggling with Time Series pattern recognition and classification problem?

I have some sensor data and it is labelled. Now I want to know how can I extract features from time series using DFT, DWT and HAAR transforms. I know that transformations above transform a signal ...
5
votes
0answers
109 views

How to model segmentation of a sequence to similar parts?

I guess LSTM is good for sequence modeling but how would you model "clustering" with it? Meaning, the input is a sequence and the output is labels with similar properties (I have labeled data). For ...
5
votes
0answers
97 views

Is Minimax Linkage a Lance-Williams hierarchical clustering?

I found the following article on "Hierarchical Clustering With Prototypes via Minimax Linkage". It is stated in Property 6 that Minimax linkage cannot be written using Lance–Williams updates. A ...
4
votes
0answers
134 views

What is difference between Multi-class One vs All and Multilabel Classification?

Although Multi class is different from Multi label classification, whats difference does adding One vs All make in Multi-class. Edit 1: http://scikit-learn.org/stable/modules/multiclass.html#...
4
votes
0answers
261 views

Clustering for high dimensional data

I am have a data set with 52 variables. Most of them have zeros, it resembles a sparse matrix. How can I cluster this kind of data and are there any special types of clustering? I am attaching pca ...
4
votes
0answers
482 views

AUC computation on multilabel classification

I'm using Tensorflow for an auto-tagging task on audio clips. The problem is actually a multilabel classification problem meaning that each clip can have multiple tags at the same time. Regarding ...
4
votes
0answers
786 views

AdaBoost implementation and tuning for high dimensional feature space in R

I am trying to implement the AdaBoost.M1 algorithm (trees as base-learners) to a data set with a large feature space (~ 20.000 features) and ~ 100 samples in R. There exists a variety of different ...
4
votes
0answers
221 views

how to propagate error from convolutional layer to previous layer?

I've been trying to implement a simple convolutional neural network. But I've been stuck at this problem for over a week. To be specific, assume there are 3 layers in a convolutional pass, marked as ...
4
votes
0answers
184 views

Human Activity Recognition - How to process gyroscope and magnetometer data

I've found many articles (like this one) on HAR that mention using the gyroscope and magnetometer because it improves the precision of HAR performed just with the accelerometer. However no one ...
4
votes
0answers
114 views

Heterodox use of Deep Learning to find hidden patterns

I would appreciate your comments/help about a strategy I am applying in one of my analysis. In short, my case is: 1) My data have biological origin, collected in a period of 120s, from a subject ...
3
votes
0answers
56 views

Training deep CNN with noisy dataset

I am training a Mask RCNN model with a train dataset that has been generated from some simple computer vision operations (color thresholding) and some morphological filtering. The train set captures ...
3
votes
0answers
37 views

How to deal with count data in random forest

I am working on a classification model where my target class is a biased class with the class shape as 0 1 20694 101 Most of my features are the ...
3
votes
0answers
32 views

Training value neural network AlphaGo style

I have been trying to replicate the results obtained by AlphaGo following their supervise learning protocol. The papers specify that they use a network that has two heads: a value head that predicts ...
3
votes
0answers
37 views

Adding recommendations to the output of a classification model

I have built a binary classification model using: logit decision trees random forest bagging classifier gradientboost xgboost adaboost I have evaluated the above models and chose xgboost based on ...
3
votes
0answers
52 views

RNN-based Predictions of Sine Waves with Frequency Different From Training Data

I am wondering if I can generate a sine wave with a frequency different from training data using RNN. For example, Using two training data of two time series, say 0[sec] ~ 10[sec] each: sin(t) and ...
3
votes
0answers
50 views

Robustness of ML Model in question

While trying to emulate a ML model similar to the one described in this paper, I seemed to eventually get good clustering results on some sample data after a bit of tweaking. By "good" results, I mean ...
3
votes
0answers
37 views

Deep Learning: Does starting the training on a smaller subset of the data make sense?

I trained a deep neural network with a small subset of my data, which allowed me to go through many epochs in a short amount of time and allowed the model to perform reasonably, then I gave it the ...
3
votes
0answers
27 views

Tuning Lexicon Sentiment-values Using Machine-learning

I'm constructing a sentiment-analysis model using the lexicon-based approach, and wondering if I can tune the weights of each word-feature in the lexicon using machine-learning. Is this achievable ...
3
votes
0answers
106 views

Machine Learning & Image Recognition: How to start?

I've been a full stack web developer for 15 years now and would like to be involved in machine learning. There is already a specific scenario for this: We have a database with several million products ...
3
votes
0answers
45 views

Predicting change of shapes/coordinates

I'm trying to find a way to predict/calculate how a shape (e.g. outline of a glacier) will change in the future—based on its history (previous shape) and additional factors (e.g. Δtemperature). In my ...
3
votes
0answers
187 views

How to properly represent a tic tac toe board to a CNN?

I'm figuring out how to manipulate convolutional neural networks (CNN) in python and I want to apply this kind of NN to an agent player that plays tic tac toe. I know that's weird and the problem ...
3
votes
0answers
33 views

Hochreiter LSTM (p. 4): Maximal values of logistic sigmoid derivative times weight

My questions follow the below page 4 excerpt from Hochreiter's LSTM paper: If $f_{l_{m}}$ is the logistic sigmoid function, then the maximal value of $f^\prime_{l_{m}}$ is 0.25. If $y^{l_{m-1}}$ ...
3
votes
0answers
1k views

ValueError: operands could not be broadcast together with shapes (60002,39) (38,) during pca.transform

I am trying to solve the San Francisco Crime Problem on Kaggle. To begin with, here is my code: ...
3
votes
0answers
26 views

Formula to calculate size of Capsule output similar to the formula for CNN?

Is there any formula to find the output dimensions of a capsule network similar to that of a Convolutional Neural Network? For Example: In CNN, we know that ...
3
votes
0answers
94 views

Confidence value in AdaBoost?

I read this introduction about AdaBoost (http://www.cs.man.ac.uk/~nikolaon/~nikolaon_files/Introduction_to_AdaBoost.pdf), and am curious why confidence for each model is defined as $$\alpha_j=\frac{...
3
votes
0answers
47 views

Deriving diagonal approximation of Hessian in a neural network

Consider the equations relating to the diagonal approximation for the hessian matrix for a neural network in "Pattern Recognition and Machine Learning - Christopher Bishop" (on pg. 250 eq. 5.80) $\...
3
votes
0answers
115 views

How to do give input to CNN when doing a text processing?

As a signal processing engineering and being new to NLP, I am confused with giving input to CNN network. With my knowledge of CNN, I am trying to build a classifier for ethnicity with inputs as text ...
3
votes
0answers
57 views

make prediction with a time serie

I want to build a model that can detect which driver is driving now the car based on a dataset that contains 20 driver records for 3600s each driver ( the dataset contains all the car sensors values ...
3
votes
0answers
353 views

Keras - Masking CNNs

I have a 3D tensor on which I apply 2D convolutions. Sometimes, this 3D is padded both in width and height to have a fixed size. How could I apply masking (like with RNNs) so that the gradients ...
3
votes
0answers
653 views

Help with the following error: Variable already exists, disallowed. Did you mean to set reuse=True in VarScope?

I am not sure how to handle this error. This is from an RNN tutorial found here. I vaguely understand that the variables need to be able to be reused, but I don't know how to implement this fix. ...
3
votes
0answers
445 views

Sales Dataset to determine best model for predicting future sales

We have a set of products in which we are trying to determine which products we should continue to sell, and which products to remove from our inventory. The file contains BOTH historical sales data ...
3
votes
0answers
70 views

which loss function (if any) optimizes the calibration graph

The calibration graph is the predicted versus actual probability(see http://scikit-learn.org/stable/modules/generated/sklearn.calibration.calibration_curve.html). Is it possible to optimize the ...
3
votes
0answers
341 views

What causes the error in a RNN to increase late in training?

I'm training a 2-layer, 1024 node, dropout of 0.5 RNN over natural text. Specifically, I'm using karpathy's char-rnn which I found to work quite well for most of my use cases. Sometimes however, late ...
3
votes
0answers
381 views

Illustrating the dimensionality reduction done by a classification or regression model

Tl;DR: You can predict something, but how do you explain the prediction? Your usual classification/regression setup Lets say the data is a classic regression/classification problem: several ...
3
votes
0answers
71 views

Train a classifier for a game with feedback on chosen move instead of true labels

I'm having some trouble describing in one line what I want, which is probably why I haven't had much luck with Google. Say I have a game like 2048 where the possible actions each step are fixed (and ...
3
votes
0answers
85 views

Is there an interface for bootstrap sampling in rattle in R?

I am using rattle in R for predictive models and am trying to see whether there is a difference in different sampling methods. The split function at the start of rattle for splitting into training and ...
3
votes
0answers
69 views

Various algorithms performance in a problem and what can be deduced about data and problem?

HI I am currently trying to apply various algorithms to a classification problem to assess which could be better and then try to fine tune the bests of the first approach. I am a beginner so I use ...
2
votes
0answers
13 views

How do I resolve this error: “expected string or bytes-like object” please?

I was doing Lemmatisation but I got the above error. I think it's because my data isn't in string form, is that correct? If so, which part of my data isn't in string form? This is my data source: ...
2
votes
0answers
16 views

Estimating location in a model

I have a big dataset with 10 columns and about a 100,000 rows. Each 5 rows represent a person being tracked and the data related to this tracking such as time, velocity, etc. the last two columns are ...
2
votes
0answers
15 views

Grouping the Input Features for LSTM (keras)

When I have a input feature of 2-dimension (variable*feature), is it still good to flatten them into 1-dimension input ...
2
votes
0answers
17 views

How to create a prediction interval with the fact that the residuals follow a specific distribution (in python)

I am looking at a software development pipeline where I am predicting the lead time of different products flowing through the pipeline. After applying a boxcox transformation on the lead time (...
2
votes
0answers
29 views

Test RMSE of polynomial regression drops when using more variables?

I am testing polynomial regression for a data set of 50 variables and a sample size of 5000. I ordered the coefficients of the linear model from high to low and then made different models using the p ...
2
votes
0answers
32 views

Audio files and their corresponding spectrograms for image classification process

Suppose I have a dataset of audio files that I have to use for whale sound classification. I am choosing the strategy of treating it as an image classification problem by using their corresponding ...
2
votes
0answers
24 views

How to force histogram plots to have same axes?

I am comparing my trained model with other benchmark models with the error histogram but the axis of histogram is different for each method as shown in figure.For instance to plot the error histogram ...
2
votes
0answers
18 views

Obtain learning curve of Gradient Boosted Tree model in PySpark

Currently there seems to be no method in PySpark of checkpointing the performance of a model at each gradient update. Is there a way to get the performance of a model at each gradient update so that a ...
2
votes
0answers
26 views

How to make machine learning model that reports ambiguity of the input?

Suppose I want to build a neural network regression model that takes one input and return one output. Here's the training data: ...
2
votes
0answers
25 views

What is the motivation for row-wise convolution and folding in Kalchbrenner et al. (2014)?

I was reading the paper by Kalchbrenner et al. titled A Convolutional Neural Network for Modelling Sentences and am struggling to understand their definition of convolutional layer. First, let's take ...