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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 ...
Matt's user avatar
  • 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. ...
AfBM's user avatar
  • 91
8 votes
0 answers
136 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 ...
Phaune's user avatar
  • 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 ...
Reward's user avatar
  • 81
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. ...
AutomaKen's user avatar
7 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 ...
Palisadoes's user avatar
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" ...
Aurast's user avatar
  • 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 ...
Varun's user avatar
  • 71
7 votes
0 answers
929 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 ...
anymous.asker's user avatar
7 votes
0 answers
513 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 = ...
ihadanny's user avatar
  • 1,357
6 votes
0 answers
143 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 ...
user87590's user avatar
6 votes
0 answers
333 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=...
Johan Gras's user avatar
6 votes
0 answers
89 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 ...
Jor_El's user avatar
  • 231
6 votes
0 answers
304 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{...
user3326682's user avatar
6 votes
0 answers
376 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 ...
Jason's user avatar
  • 61
6 votes
0 answers
97 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 ...
John Karimov's user avatar
6 votes
0 answers
136 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\...
David Silver's user avatar
6 votes
0 answers
607 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 ...
ethelion's user avatar
6 votes
0 answers
230 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 ...
tom's user avatar
  • 2,238
6 votes
0 answers
3k views

How to tune weights in Voting Classifier (Sklearn)

I am trying to do the following: ...
Abhinav Gupta's user avatar
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 ...
Daniel Underwood's user avatar
6 votes
0 answers
110 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 ...
Jan Wrona's user avatar
6 votes
0 answers
12k 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: ...
user1877600's user avatar
6 votes
0 answers
290 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 ...
Shindou's user avatar
  • 161
6 votes
0 answers
100 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 ...
André Soares's user avatar
6 votes
0 answers
367 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). ...
Minu's user avatar
  • 795
5 votes
0 answers
83 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 ...
Jozef Nagy's user avatar
5 votes
0 answers
771 views

sklearn FutureWarning message when running a CNN model

When I run my model, I am receiving the following error message: ...
Jack's user avatar
  • 155
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 ...
Carlos Mougan's user avatar
5 votes
0 answers
1k views

Tensorflow, Optimizer.apply_gradient: 'NoneType' object has no attribute 'merge_call'

My program gives the following error message: ...
Kehrwert's user avatar
  • 163
4 votes
0 answers
250 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 ...
itisyeetimetoday's user avatar
4 votes
0 answers
67 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 ...
GregOliveira's user avatar
4 votes
0 answers
252 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. ...
alex-uarent-alex's user avatar
4 votes
0 answers
158 views

Fast PR / ROC curves and corespondings AUPR / AUROC

I find myself in a position of calculating numerous PR / ROC curves and their associated area under the PR curves (AUPR) / area under the ROC curve (AUROC). Its is quite easy to perform those ...
Lucas Morin's user avatar
  • 2,093
4 votes
0 answers
183 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 ...
Peter's user avatar
  • 7,426
4 votes
0 answers
599 views

How to use a ragged tensor with a convolutional layer?

I have textual data of various lengths for which ragged tensors seems well suited. For instance my data could look as follows : ...
pierre_sendorek's user avatar
4 votes
0 answers
652 views

Embedding variable length "multi-hot-encoded" features

How can I implement an embedding layer in Keras that takes in an input that could have a variable length? For instance, if the vocabulary was 10-long I could have inputs like: ...
AAC's user avatar
  • 509
4 votes
0 answers
2k 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}...
Icyblade's user avatar
  • 4,326
4 votes
0 answers
438 views

Spatial Transformer Networks and Data Augmentation

We are all familiar with the famous Deep Mind paper STN. Upon implementation, such as here, did anyone still use input data augementation such as affine transformations? There are used to make CNN ...
Benedict K.'s user avatar
4 votes
0 answers
61 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 ...
Sal9K's user avatar
  • 41
3 votes
0 answers
107 views

Why is multiple imputation not used more widely in Data Science?

I have a background in statistics. Multiple imputation is very commonly used to handle missing data, and if it is not used it almost always results in serious criticism. Recently I have been ...
Joe King's user avatar
  • 141
3 votes
0 answers
71 views

Where can I find implementation of the various improvements of K-nearest neighbors (KNN)?

I have been facing some challenges where traditional KNN algorithm perform well. I'd like to explore more advanced knn solutions. While researching possible solutions, I came across a paper titled <...
Lucas Morin's user avatar
  • 2,093
3 votes
0 answers
393 views

Text embeddings for words or very short sentences with a LLM

I tried to compute the semantic similarity between words or short sentences. Ex : inflation vs price raising I have tried the openai embeddings API and cosine distance but the results are very poor. I ...
user2479920's user avatar
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 ...
Ram Rachum's user avatar
3 votes
0 answers
223 views

Multi-dimensional Euclidian R^2 squared - reasonable?

I have a high-dimensional space, say $\mathbb{R}^{1000}$, and I have samples $y_1, \ldots , y_n \in \mathbb{R}^{1000}$ and $\hat{y}_1, \ldots , \hat{y}_n \in \mathbb{R}^{1000}$. Would $$ R^2 = 1 - \...
AspiringToAspire's user avatar
3 votes
0 answers
123 views

Intuitively, why do Non-monotonic Activations Work?

The swish/SiLU activation is very popular, and many would argue it has dethroned ReLU. However, it is non-monotonic, which seems to go against popular intuition (at least on this site: example 1, ...
Jason's user avatar
  • 53
3 votes
0 answers
296 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 ...
Michael's user avatar
  • 131
3 votes
0 answers
39 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 ...
duy quan duc's user avatar
3 votes
0 answers
1k views

Differences between Feature Importance and SHAP variable importance graph

I have run an XGBClassifier using the following fields: ...
Giampaolo Levorato's user avatar
3 votes
0 answers
55 views

Understanding Kneser-Ney Formula for implementation

I am trying to implement this formula in Python $$ \frac{\text{max}(c_{KN}(w^{i}_{i-n+1} - d), 0)}{c_{KN}(w^{i-1}_{i-n+1})} + \lambda(c_{KN}(w^{i-1}_{i-n+1})\mathbb{P}(c_{KN}(w_{i}|w^{i-1}_{i-n+2})$$ ...
Wolfy's user avatar
  • 237

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