All Questions
8,422
questions with no answers
9
votes
0
answers
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 ...
- 199
9
votes
0
answers
2k
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. ...
- 91
8
votes
0
answers
120
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 ...
- 101
8
votes
0
answers
3k
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 ...
- 81
7
votes
0
answers
9k
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-...
- 696
7
votes
0
answers
3k
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.
...
- 71
7
votes
0
answers
1k
views
Multivariate, multistep forecasting with LSTM
I want to use an RNN with LSTM to forecast multiple steps into the future, based on multiple inputs. I have some ideas for different ways to approach this, but I'm afraid I'm missing the "right way" ...
- 171
7
votes
0
answers
2k
views
Fine tuning accuracy lower than Raw Transfer Learning Accuracy
I've used transfer learning on Inception V3 with ImageNet weights on Keras with Tensorflow backend on python 2.7 to create an image classifier. I first extracted and saved the bottleneck features from ...
- 71
7
votes
0
answers
913
views
ALS in Spark: what loss function is it minimizing?
I’ve playing with the MovieLens ratings dataset under Spark’s ALS and a manual implementation of ALS and comparing results with the same hyperparameters. I’d like to know this exactly in order to make ...
- 834
7
votes
0
answers
508
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 = ...
- 1,347
6
votes
0
answers
128
views
Unable to transform (greatly performing) Autoencoder into Variational Autoencoder
Following the procedure described in this SO question, I am trying to transform my (greatly performing) convolutional Autoencoder into a Variational version of the same Autoencoder. As explained in ...
- 61
6
votes
0
answers
322
views
Optimal implementation of vanilla DQN loss in Keras
I've implemented vanilla DQN for continuous/non-images (no CNN) states in keras. But, I'm not sure if my implementation of the loss computation is optimal.
For reminder the loss is defined as : $loss=...
- 61
6
votes
0
answers
76
views
Fitting model to differenced time series
I have a time series on daily stock price of company(2013 data points).I took a first order difference and the following acf and pacf plots of the differenced series were obtained. However, I am ...
- 231
6
votes
0
answers
2k
views
Using the Python Keras multi_gpu_model with LSTM / GRU to predict Timeseries data
I'm having an issue with python keras LSTM / GRU layers with multi_gpu_model for machine learning.
When I use a single GPU, the predictions work correctly ...
- 161
6
votes
0
answers
2k
views
What is the minimum number of times a word needs to appear in word2vec training corpus for quality results?
When training a word2vec model with, eg, gensim, you can specify the minimum times a word needs to be seen (with the parameter min_count). The default value for this seems to be 5.
Are there any ...
- 193
6
votes
0
answers
279
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{...
- 143
6
votes
0
answers
362
views
Maths of Xavier initialization
The paper I read is Glorot et al (2010). And the math part is in Section 4.2.1.
Formula (5) and (10) make sense to me but I cannot derive formula (6) and (7) myself from (2) and (3).
I found many ...
- 61
6
votes
0
answers
91
views
Classify driver based on time-series sensor data
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 ...
- 61
6
votes
0
answers
124
views
Learning a logical function with a 2 layer BDN network - manual weight setting rule question?
So I am trying to construct a 2-layer network of binary decision neurons as proposed by McCullough and Pitts (1943) to learn a logical function (a composition of AND's and OR's) such as:
$((\neg x_1\...
- 61
6
votes
0
answers
599
views
Adversarial Learning for Semantic Segmentation
I am incorporating Adversarial Training for Semantic Segmentation from Adversarial Learning for Semi-Supervised Semantic Segmentation.
The idea is like this:
The discriminator takes as input a ...
- 61
6
votes
0
answers
225
views
Connect output node to next hidden node in RNN
I'm trying to build a neural network with an unconventional architecture and a having trouble figuring out how. Usually we have connections like so, where $X=$ input, $H=$ hidden layer, $Y=$ output ...
- 2,188
6
votes
0
answers
3k
views
6
votes
0
answers
1k
views
Keras objective function shared between outputs
Is there any way to implement a loss function that is shared between outputs? I have a 2D image output and scalar classification that are both used by a single loss function.
I have attempted writing ...
- 161
6
votes
0
answers
107
views
Fixed-radius range search in non-Euclidean space
I'm trying to find an indexing data structure most suitable for my metric space:
set of IP network related data (IP addresses, ports, TCP flags, ...),
distance function is continuous, non-Euclidean ...
- 61
6
votes
0
answers
11k
views
Tuning Gradient Boosted Classifier's hyperparametrs and balancing it
I am not sure if it is a correct stack. Maybe I should have put my question into crossvalidated.
Nevertheless, I perform following steps to tune the hyperparameters for a gradient boosting model:
...
- 286
6
votes
0
answers
287
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 ...
- 161
6
votes
0
answers
99
views
Meta-analysis of public 16S data
I am trying to start a meta-analysis for which I want to extract some 16S-based information from public databases. Moreover, I want to relate this information with any metadata found in the associated ...
- 161
6
votes
0
answers
332
views
3D map using leaflet
I'm trying to create 3D bars on this map. Can anyone please advise if this is possible, and how?
http://leafletjs.com/examples/choropleth.html
My data: UFO sightings in the USA (location wise).
...
- 795
5
votes
0
answers
80
views
How is image convolution actually implemented in deep learning libraries using simple linear algebra?
As a clarifier, I want to implement cross-correlation, but the machine learning literature keeps referring to it as convolution so I will stick with it.
I am trying to implement image convolution ...
- 51
5
votes
0
answers
730
views
sklearn FutureWarning message when running a CNN model
When I run my model, I am receiving the following error message:
...
- 145
5
votes
0
answers
2k
views
Dealing with categorical variables in Isolation Forest
Isolation Forest is widely used when dealing with outlier/anomaly detection when we have no labels. The theory behind is that making random split at random points and counting how many splits you do ...
- 5,841
5
votes
0
answers
1k
views
Tensorflow, Optimizer.apply_gradient: 'NoneType' object has no attribute 'merge_call'
My program gives the following error message:
...
- 163
4
votes
0
answers
137
views
How Does the Reward Model in ChatGPT Calculate Losses?
Reading the InstructGPT paper(which seems to be what ChatGPT was built off of), I found this equation for the reward function.
However, I'm struggling to understand how this equation is used to ...
- 141
4
votes
0
answers
55
views
Does ROC AUC different between crossval and test set indicate overfitting or other problem?
I am training a composite model (XGBoost, Linear Regression, and RandomForest) to predict injured people probability. Well, the results of cross-validation with 5 folds. Well, I can see any problem ...
- 116
4
votes
0
answers
202
views
ResNet50 + Transformer
In many papers people extract features from image using ResNet and than pass them through transformer. I want to implement the same. I want to get features and than classify them using transformer. ...
4
votes
0
answers
161
views
Bag of words: Prediction on new (out-of-sample) data
I'm working with a bag of words in R:
library(tm)
corpus = VCorpus(textsource)
dtm = DocumentTermMatrix(corpus)
dtm = as.matrix(dtm)
I use the matrix ...
- 7,247
4
votes
0
answers
1k
views
How to train continuous/soft classification model?
The classic classification problem is like finding the function $F:\mathbb{R}^n\mapsto \{0,1\}$. The label set will be [Apple,Banana,Banana,...,Apple].
What if I want to train a function $F:\mathbb{R}...
- 4,226
4
votes
0
answers
60
views
Image grid - labels?
I was wondering if labels could be visualized below images in the image grid tool in Image Analytics?
I know, this feature might be not terribly useful for images in general, hence unlikely to be ...
- 41
3
votes
0
answers
51
views
Public data set with exciting data
I'm going to give a talk about a tool for viewing tabular datasets. I'll first give this talk at a meetup, then hopefully at a series of conferences over the next few years.
I want to demonstrate to ...
- 255
3
votes
0
answers
3k
views
What are the "EMA" weights included with certain pre-trained models?
I came across this machine learning model called "Stable Diffusion v1." When downloading the pre-trained weights for this model, I noticed that there's a couple of different files:
...
- 131
3
votes
0
answers
208
views
Why is NDCG high even for wrongly ranked predictions?
The NDCG (Normalized Discounted Cumulative Gain) metric for ranking is defined as DCG/IDCG, where IDCG is the ideal DCG and is said to take values in [0, 1].
However, since the DCG will always be ...
- 131
3
votes
0
answers
35
views
Can we recognize different events in time-series data by patterns?
I'm currently have to deal with multiple time-series datasets with the same type of patterns. My quest is to find a way to label these data points (or may be intervals) correctly. Below is how the ...
- 31
3
votes
0
answers
48
views
Understanding Kneser-Ney Formula for implementation
I am trying to implement this formula in Python
$$ \frac{\text{max}(c_{KN}(w^{i}_{i-n+1} - d), 0)}{c_{KN}(w^{i-1}_{i-n+1})} + \lambda(c_{KN}(w^{i-1}_{i-n+1})\mathbb{P}(c_{KN}(w_{i}|w^{i-1}_{i-n+2})$$
...
- 237
3
votes
0
answers
55
views
Is it Scientifically Rigorous to create a multimodal ML Model with data from multiple sources
I'm attempting to create a multimodal machine learning model for disease diagnosis. However, I'm having quite a bit of difficulty finding public data sets with all the data I need.
For example, I need ...
3
votes
0
answers
18
views
Homework/class help: Backward propagation of max pooling if each element in an array determines more than one value?
(This isn't actually my homework, and in fact wasn't addressed in my homework, but I was confused about this because my homework hadn't addressed this)
For example if I have an array:
And I do max ...
- 31
3
votes
0
answers
1k
views
Identify MCAR, MNAR and MAR in the data
If I have missing values in a dataset, I can't just blindly impute them with mean/median/mode or any other technique. I have to identify what kind of missing values they are, namely:
MCAR (missing ...
- 1,576
3
votes
0
answers
180
views
Why margin loss is used in Capsule Network instead of Cross Entropy loss?
I'm reading the Capsule Network paper proposed by Hinton. I'm not sure why the margin loss is used instead of the cross entropy loss. Any intuitive explaination for this?
- 131
3
votes
0
answers
125
views
Non-greedy decision tree / random forest implementation(s) in Python
The standard random forest is trained using a greedy approach for computational feasibility. However, there are a number of alternative methods such as "lookahead" or using bilevel ...
- 7,247
3
votes
0
answers
839
views
Forecast Model to Estimate Customer Service Call Volume and Appropriate Staff
I am working on a project to predict the proper staffing needed for a customer service team using historical data.
I am new to machine learning, and I am not sure if my approach to this problem is the ...
- 31
3
votes
0
answers
30
views
How to train a neural network where computing the loss requires multiple object values?
I want to train a function that given metadata about an image produces hyper-parameters for an algorithm which operates on the image.
My understanding is (please forgive me I'm a novice here) a neural ...
