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15
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0answers
292 views

Formal proof of vanilla policy gradient convergence

So I stumbled upon this question, where the author asks for a proof of vanilla policy gradient procedures. The answer provided points to some literature, but the formal proof is nowhere to be included....
12
votes
0answers
2k views

Understanding Timestamps and Batchsize of Keras LSTM considering Hiddenstates and TBPTT

What I'm trying to do What I am trying to do is predicting the next data-point $x_t$ for each point in the timeseries $[x_0, x_1, x_2,...,x_T]$ in the context of a date-stream in real-time, in theory ...
11
votes
1answer
382 views

ngram and RNN prediction rate wrt word index

I tried to plot the rate of correct predictions (for the top 1 shortlist) with relation to the word's position in sentence : I was expecting to see a plateau sooner on the ngram setup since it ...
9
votes
2answers
124 views

Generating images meshing up different shapes with a deep learning software automatically

My pursuit is to generate something like a grottesque(a kind of painting producing human-animals and plants hybrids). I need to do something like this painting in order to create an art exhibition. I ...
9
votes
2answers
874 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 $x_i$...
8
votes
2answers
1k views

Loss Function for Probability Regression

I'm trying to predict a probability with a neural network, but having trouble figuring out which loss function is best. Cross entropy was my first thought, but other resources always talk about it in ...
8
votes
2answers
1k views

Forecasting Multiple (few hundreds) uni-variate time series with inflated zeros

Hello Practitioners, Being a newbie seeking help to gain experience in Data Science. Lets take a scenario where a big company wants to forecast its sales (a specific product) across different stores ...
7
votes
1answer
137 views

bias and variance trade off related question

I am having difficulty to understand the expected squared errors formula in this website: $y=f(x)+e$ true regression line $\hat{y}=\hat{f}(x)$ your estimated regression line $error(x)=\bigg(\...
7
votes
0answers
1k 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. ...
6
votes
0answers
67 views

XGBoost skews towards minority class

I have a dataset with 85k positive labels and 53k negative labels. For this use-case, I am trying to maximize my efforts to the negative class (accurately identify true negatives, and minimize false ...
6
votes
0answers
147 views

ground truth fit is worse than cross validated fit on noisy data?

I am having these weird results when playing around with cross validation that I would greatly appreciate to have any comments. Briefly, I have a lower mean squared error (MSE) when doing regression (...
6
votes
0answers
151 views

Are there any graph embedding algorithms like this already?

I wrote an algorithm for generating node embeddings based on the graph's topology. Most of the explanation is done in the readme file and the examples. The question is: Am I reinventing the wheel? ...
6
votes
0answers
138 views

When is the sum of models the model of the sum?

The response variable in a regression problem, $Y$, is modeled using a data matrix $X$. In notation, this means: $Y$ ~ $X$ However, $Y$ can be separated out into different components that can be ...
6
votes
0answers
8k views

How is WordPiece tokenization helpful to effectively deal with rare words problem in NLP?

I have seen that NLP models such as BERT utilize WordPiece for tokenization. In WordPiece, we split the tokens like playing to play and ##ing. It is mentioned that it covers a wider spectrum of Out-Of-...
6
votes
0answers
2k views

Why is my Keras model not learning image segmentation?

Edit: as is turns out, not even the model's initial creator could successfully fine-tune it. This is most likely a problem of implementation, or possibly related to the non-intuitive way in which the ...
6
votes
1answer
183 views

Training stateful LSTM with different number of sequences

I'm using a stateful LSTM for stock market analysis, and I have varying amounts of data for each stock, ranging from 20 years to just a few weeks (i.e. for newly listed stocks). I use 3 years of data ...
6
votes
1answer
324 views

Chi-square as evaluation metrics for nonlinear machine learning regression models

I am using machine learning models to predict an ordinal variable (values: 1,2,3,4, and 5) using 7 different features. I posed this as a regression problem, so the final outputs of a model are ...
6
votes
0answers
2k views

Python : Feature Matching + Homography to find Multiple Objects

I'm trying to use OpenCV via Python to find multiple objects in a train image and match it with the key points detected from a query image. For my case, I'm trying to detect the tennis courts in the ...
6
votes
1answer
326 views

Visualizing 28 different variables with 28 different colors?

ColorBrewer seems to be very useful in selecting a color pallet to represent factors that have up to 12 possible values. I have 28. Is it a horrible idea to represent 28 variables with color? If so,...
6
votes
1answer
419 views

A clear visualization of a two-way ANOVA

To provide a full yet simple picture of a 3-level, one-way ANOVA, I use the following visualization where variation within each group (the filled circles) and variation between the groups (black ...
6
votes
0answers
916 views

Comparing transition matrices for Markov chains

I have a population, each unit of which exists in one of several states that change over time. I am using first-order Markov chains to model these state transitions. My population can be segmented ...
5
votes
3answers
77 views

How can data science teams inside businesses measure costs and efficiency of their technical work?

How can data science teams measure and improve costs of their technical work, when they often don't know the monetary value of the datasets and insights they are producing? Are they using industry ...
5
votes
0answers
129 views

How to achieve SHAP values for a CatBoost model in R?

I'm asked to create a SHAP analysis in R but I cannot find it how to obtain it for a CatBoost model. I can get the SHAP values of an XGBoost model with ...
5
votes
1answer
54 views

N-grams for RNNs

Given a word $w_{n}$ a statistical model such a Markov chain using n-grams predicts the subsequent word $w_{n+1}$. The prediction is by no means random. How is this translated into a neural model? I ...
5
votes
2answers
61 views

Data transformations in hierarchical classification

I am building a hierarchical text classifier using the Local Classifier Per Parent Node (LCPN) approach with the 'siblings' policy as described in the A survey of hierarchical classification across ...
5
votes
1answer
4k views

Keras - Implementation of custom loss function with multiple outputs

I am trying to replicate (a way smaller version) of the AlphaGo Zero system. However, in the network model, I am having a problem. The loss function I am supposed to implement is the following: $$l = ...
5
votes
2answers
125 views

Cluster evolution over time

I have a dataset of transactional data with customer ID and I want to segment the dataset into groups using cluster analysis. I'm interested in following the evolution of each cluster over time, but ...
5
votes
1answer
60 views

Detecting abundance of a certain periodic pattern in a time series?

I am really stumped at the moment about how to solve a particular problem. I have many time series like this: This represents the number of hours a person spends on a website each day throughout the ...
5
votes
0answers
423 views

Gensim LDA model: return keywords based on relevance (λ - lambda) value

I am using gensim library for topic modeling, more specifically LDA. I have created my corpus, my dictionary and my lda model, and with the help of pyLDAvis library I visualize the results. When I ...
5
votes
2answers
93 views

How to interpret two continous variables output using GAM?

I really need help with GAM. I have to find out whether association is linear or non-linear by using GAM. The predictor variable is temperature at lag0 and the output is cardiovascular admissions (...
5
votes
1answer
278 views

Pyspark: Filter dataframe based on separate specific conditions

How can I select only certain entries that match my condition and from those entries, filter again using regex? For instance, I have this dataframe (df) ...
5
votes
0answers
149 views

How to implement hierarchical labeling classification?

I am currently working on the task of eCommerce product name classification, so I have categories and subcategories in product data. I noticed that using subcategories as labels delivers worse results ...
5
votes
0answers
2k views

Tensorflow v1 Dataset API AttributeError with ndim

I'd like to make pipeline for optimizing Gpu and Cpu. Dataset It's about 10000 datapoint and 4 description variables for the regression problem. ...
5
votes
0answers
58 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 ...
5
votes
2answers
541 views

Image recognition of selfie images

I developed an Android app that lets anyone upload pictures of encyclopedic things (bridges, museums, dishes, landscapes, paintings, etc) to Wikimedia Commons. Unfortunately, 5% of the users find it ...
5
votes
2answers
257 views

Text topic classification in tensorflow

I want to create a CNN in tensorflow that does the following: Classify a recipe headline and find out the topic. For instance <...
5
votes
1answer
1k views

Implementing spatio-temporal convolutions in pytorch

I am trying to implement a layer to perform the (2+1)D convolutions described in this paper: https://arxiv.org/pdf/1711.11248.pdf The basic idea is as follows: Let's say I have a 3D convolutional ...
5
votes
0answers
2k views

Loss function for optimising precision & recall / sensitivity & specificity?

I've been using precision and recall as my metrics, as per keras-team/keras/pull/9393/files Sensitivity & specificity is what I want to optimise for. Every epoch I output it: ...
5
votes
3answers
511 views

Hyperparameter tuning in multiclass classification problem: which scoring metric?

I'm working with an imbalanced multi-class dataset. I try to tune the parameters of a DecisionTreeClassifier, ...
5
votes
1answer
167 views

Methods for ensembling ranked lists?

I was wondering if there's a good way to use ensembling when I have two or more algoritims producing ranked lists. That is, suppose I have the following datasets consisting of ordered lists (higher ...
5
votes
0answers
1k views

How to tune weights in Voting Classifier (Sklearn)

I am trying to do the following: ...
5
votes
1answer
639 views

Time Series pattern recognition and classification problem

I have some labeled sensor data. Now, I would like to know how to extract features from time series using DFT, DWT, and HAAR transforms. I know that the transformations above transform a signal to ...
5
votes
1answer
134 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
2answers
297 views

Changing default values of ANNIE resources in GATE from Java code

In GATE, default values for ANNIE are set during initialization, but sometimes based on requirements they have to be changed. My Requirement : I want to extract English sentences without considering ...
5
votes
0answers
478 views

differences between LSQR and FTRL when working with very sparse data

I have a 2M instances dataset with millions of very very sparse dummy variables created using the hashing trick = ...
4
votes
1answer
72 views

YOLOv1 algorithm - how to determine predictor responsibility

I am researching Yolo detector, and have read the original paper, but still have some confusion and a few questions regarding the assignment of bounding box predictors to ground truth at training time ...
4
votes
0answers
61 views

Can one perform Feature Selection on a subset of training data?

I have a training data set with almost one million rows and I am considering eight features initially. My machine learning model will be Random Forest regressor. In Section 3.4.7 of "Feature ...
4
votes
1answer
53 views

What ML architecture fits fixed length signal regression?

My problem is of regression type - How to estimate a fish weight using fixed length signal (80 data points) of the change in resistance when the fish swim through a gate with electrodes (basically 4 ...
4
votes
0answers
154 views

XGBoost custom objective for regression in R

I implemented a custom objective and metric for a xgboost regression task. In order to see if I'm doing this correctly, I started with a quadratic loss. The ...
4
votes
0answers
43 views

Repeated k-fold Cross Validation for time series data?

I have a relative small sample size (330 with 45 features) + it's time series data. I want to train my LightGBM regression model for best generalized RMSE score and want to use repeated CV. I use ...

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