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Questions tagged [tensorflow]

TensorFlow is an open source library for machine learning and machine intelligence. TensorFlow uses data flow graphs with tensors flowing along edges. For details, see https://www.tensorflow.org. TensorFlow is released under an Apache 2.0 License.

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Getting nearly 100% accuracy using Binary Classification in Tensorflow but incredibly wrong prediction levels for email messages

I'm creating a Chrome Extension to read user emails via Gmail's API, and then passing in user emails to a trained Keras model in Flask to determine whether the email was written by an AI or a Human, ...
Chibuike S. Eze's user avatar
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Overfitting - Imbalance Classification using Deep-feed forward network

I have an unbalanced dataset, so I used SMOTEENN on the training set to resample, after training DFF,i could see the model is overfitting, could someone help me solve this? Thank You. ...
Pavithra K's user avatar
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Why the f1 score on validation dataset significantly higher than f1 score on testing dataset?

I'm using a TensorFlow model that look likes this: ...
Furno's user avatar
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Tensorflow SegNet architecture

I was unable to find a complete description of the SegNet architecture for image segmentation (specifically, the decoder layers). Therefore, I would like to clarify the correctness of my ...
D .Stark's user avatar
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I want to send parallel inputs to LSTM layers each LSTM layer should recieve 60 timesteps of single feature. How should i shape my inputs

...
Shreedatta Nasik's user avatar
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(Tensorflow) How to speed up initialization of model.fit()?

So I'm working with a rather large dataset (perhaps not really by ML standards - but too big to fit into my computer's RAM at any rate). And so, I train the model by successively loading a subsample ...
Tom P's user avatar
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How to Balance Dataset extracted using image_dataset_from_directory

I'm new to tensorflow, so I've been trying to find the best way to do class balancing over a dataset where I used image_dataset_from_directory to load. But I haven't find the way to do it. I saw from ...
lopez-mgu's user avatar
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Can someone interpret my Binary Cross Entropy Loss Curve?

I am trying to understand my loss curve using : tf.keras.losses.BinaryCrossentropy() Question 1: Based on my loss curve/accuracy, would it be wise to proceed to feed it into a ensemble learning model ...
Leibon Jarbis's user avatar
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Lost when trying to get good time series prediction results (regression problem) even after trying many things

I'm not able to get good results after a long time testing when using TensorFlow to predict time series data (regression problem). I don't know if the problem is with the data (little quantity and/or ...
Marco's user avatar
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Do LSTM, GRU and Transformer models with less layers and units perform better than larger models when classifying short text sequences?

I am working with a Kaggle dataset with short Twitter messages as text input. I made a copy here. When testing LSTMS, GRUs, bi-directional versions of the GRUs, and the Encoder layers of a Transformer ...
Joachim Rives's user avatar
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How can I change my input shape in the architecture for the cnn(transfer learning)?

I have already made a model and trained it, and then saved the model along with its weights. The input shape in that model is [900,300,1] which is [height,width,channel]. I want to use the same model ...
beschichtung346's user avatar
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Tensorflow keras training/validation loss digits of precision

I have my model defined with certain structure and now just permuting between filter counts and number of layers of structure. I am watching the output of model.fit() such as ...
user2624395's user avatar
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Trained model on cifar10 performs poorly on real images

So I'm trying to train a model using the CIFAR10 dataset. The problem is that while the performance of the model on validation and test sets are good (about 95-96%), the model fails to predict images ...
AlbertDang's user avatar
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Using a neural network to predict disease outcomes in individual cases

I'm working on a research project with the goal of using a neural network to predict disease outcomes for patients. I've built a neural network using Tensorflow and Keras and I've trained and tested ...
Daniel Tveten's user avatar
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How do I automate testing and comparison of the performance of models with different layer depths, layer types, and unit counts?

I am testing the effects of different layer counts/depths, unit counts, and layer types for natural language processing. I made a Kaggle notebook where I manually create different layers and then ...
Joachim Rives's user avatar
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CNN to estimate a density map of an image, used to predict the object count

I'm trying to count the number of objects (larvae in this case), from a video. The constraint is, I cannot use any ML model, nor can I train my dataset as there are no annotations available. This ...
driver's user avatar
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Method for Combining Text Embeddings and Numeric Features in Deep Learning

I'm working on a deep learning model in TensorFlow to predict if two records within a database refer to the same person. I'm trying to use text features (in the form of embeddings) and numeric ...
jgolliher's user avatar
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Aside from trial and error, how do I select the number of layers and unit counts for LSTMS, GRUs, and Transformer units for text and time series?

When deciding on the number of units and layers for text processing or time-series prediction I rely heavily on trial and error. First, I look for a reference or paper on the topic such as the white ...
Joachim Rives's user avatar
1 vote
1 answer
50 views

Why my simple resnet model overfit?

I work on data classification. My train results are good 90%+ accuracy, but the test accuracy/loss is inconsistent. I don't succeed to get rid of the overfitting. The images are grouped, so to ...
J. Doe's user avatar
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Low Precision of LeakyReLU

Dear TensorFlow experts, I am trying to understand the following output of the TensorFlow LeakyReLU function, which seems to have very low precision: ...
Anna Christine's user avatar
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How to make my validation plots more stable and improve R2 metric?

I'm working on predicting 4 numeric values basing on signal spectrum (spectrum is represented as an array of 800 numeric values in scale 0 to 1). The input values are scaled by using StandardScaler. ...
mkow93's user avatar
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How to get the closest samples to time series dataset?

I have a deep learning time series classification model. I want to understand if the model failed to classify, due to missing or incorrupt training inputs. For simplicity let's say we have a training ...
user3668129's user avatar
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2 answers
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Difference between (None, 2000, 8) and (2000, 8)

Input: a tensorflow dataset with 17000 items: ...
Fabi's user avatar
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How to add a new item in the embeddings vocabulary?

Imagine you have trained a model containing an Embedding layer. Your model performs well and you're happy with your embedding. Then, suddenly, you want to add a new item in your vocabulary. In other ...
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Is it fair to say that Hausdorff Distance (HD) focuses on low level details while dice score (DSC) high level

I wonder if its make sense to say that Hausdorff Distance (HD) measures low-level details while dice score (DSC) focuses on high levels. If you could cite a paper, I would appreciate it.
user836026's user avatar
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How to automate the restarting of training of deep learning model in TensorFlow

I am trying to automate the (recursively) restart of a finished deep-learning training session in TensorFlow. Currently, to restart I am manually restarting my kernel and re-running the training code. ...
user10529827's user avatar
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Neural network does not overfit my data. (Primarily linear function)

I am using TensorFlow and Keras. My goal is to approximate a primarily linear function that is partially nonlinear, such that a linear regression yields a Mean Absolute Error (MAE) of 0.13. All ...
Maxim Maximov's user avatar
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20 views

Keras DNN outputs the same value over and over

I'm creating an ensemble of NNs with the same architecture, but each NN only outputs one value when given X_test data. The data (continuous values transformed to be [-1,1]) yields results as expected ...
quasimodo's user avatar
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1 answer
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How does tensorflows's session.run's fetch argument can be an output of another function, without declaring that output's name as a placeholder

I have the following code that I have simplified: ...
user_04248753498's user avatar
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1 answer
33 views

Object localization and text extraction using VGG

I'm new to Computer Vision and training a TensorFlow neural network using VGG16. The problem is quite simple: I'm training in a custom dataset to detect and localize numbers in a 100x100 image. The ...
zoddin's user avatar
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how does sigmoid activation implementation in tensorflow works?

I am running the following mnist implementation: ...
dsb's user avatar
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Training Loss for Classification Model Isn't Decreasing

I'm currently building a video classification model for engagement detection but I'm having some trouble training it. The model takes in two tensors as inputs: a 10x48x48x1 tensor which holds a stack ...
snowball's user avatar
1 vote
1 answer
56 views

How to balance labeled datas and then carry out execution with a certain ratio?

I'm building a binary classification model using a neural network, with python and the libraries tensorflow and keras. For that I have an unequal amount of labeled data: Around 2'000'000 labeled with <...
user155518's user avatar
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Convolutional Neural Network for Forecasting Video, 3 Dimensional Data, 2 Spatial Dimensions, 1 Time Dimension, Tensorflow

If we have data with 2D RGB images ordered in time, how can they be fed into a CNN? Are there 4d arrays or something like multidimensional pandas Dataframes compatible with TensorFlow. The output, I ...
user22233907's user avatar
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81 views

Empty Confusion Matrix and Zero Precision/F-score

Could you please say why I'm getting this warning while doing a binary classification using Artificial Neural Networks? The data are colored images. ...
Totoro's user avatar
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1 vote
1 answer
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TensorFlow LSTM model with lower epoch loss, but higher average RMSE. How/why?

I am very perplexed by the lower loss but higher RMSE: Here's a newer model with better loss scores on the same dataset and many predictors: ...
user2205916's user avatar
1 vote
0 answers
17 views

Averaging Weights of Identical LSTM Models for a Unified Global Model

I'm currently working on a project where I have several pre-trained LSTM models, all with the same architecture. My goal is to combine these models into a single global model by averaging their ...
albi_z8's user avatar
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1 answer
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Why the training accuracy stays high but validation accuracy does not change?

I have a binary classification problem. I get ROI mammogram images and then apply a decomposition algorithm and as output I get 5 images which summation of them results in the original image. Now, ...
Nmgh's user avatar
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1 answer
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CNN training accuracy flatlines

I'm training a CNN from scratch to do tagging of images. And my training is going nowhere. I was hoping someone could help me identify an obvious error. I would like to end up with a network that ...
laslowh's user avatar
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Regarding TextVectorization reserved tokens

From the documentation of TextVectorization: max_tokens: Maximum size of the vocabulary for this layer. This should only be specified when adapting a vocabulary or when setting pad_to_max_tokens=...
Enk9456's user avatar
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Is there a Tensorflow built-in function to create a matrix from a single-layered feedforward neural network without activation functions?

In Tensorflow, I implemented a simple single-layer feedforward neural network with N inputs and N outputs without activation functions and biases. Simply, it is just a N-by-N matrix. Question: is ...
H.C.'s user avatar
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What may cause the CNN layer weight regularizer to reduce the model accuracy

What may cause the accuracy reduction when using the tf.keras regularizer at layers in CNN in the symptom? The example is simple but it happens with more complex CNN causing no improvement during the ...
mon's user avatar
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Loss values seem to fluctuate, yet the weights are correct

I'm taking my first steps with tensorflow (and in ML in general), and using this piece of code to train a very simple model that tries to find the underlying linear relation: f(x,y) = 4x +7y -2 (+ ...
Stars's user avatar
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1 vote
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How do I best approach a multiple-target binary classification in Tensorflow/Keras?

I currently have eight features which are either categorical or continuous variables. My targets are many (~1000) binary variables. So far I have attempted skmultilearn and sklearn.multioutput. I ...
FoolsGold1997's user avatar
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Tensorflow RNN - implementing recursive layer

I am dealing with a regression problem, for which I wanted to try to use a recurrent neural network. The general setting is that I have to predict a continuous quantity starting from the evolution, in ...
ChristianC's user avatar
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Feedforward Deep neural networks

Hello everyone can you help me to create a diagram for these F-DNN ...
Veertud Tv's user avatar
1 vote
1 answer
90 views

activation=tf.keras.activations.relu vs activation='relu'

Both models are for binary classification problems Model 1 ...
Justin Jonany's user avatar
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1 answer
37 views

Confusion with tensorflow's Sequential Dense Layers

I'm working on a regression probem using Tensorflow, and have created two models with slight differences in their first Dense layer. The Models ...
Justin Jonany's user avatar
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2 answers
43 views

Binary classification using RNN not going beyond 50% accuracy

I am trying to find out the reason behind why my RNN network won't go beyond 50% for binary classification. My input data is of the shape: ...
Prabhjot Singh Rai's user avatar
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Why does the AutoKeras NAS require reshaping of data?

Please take a look at the following source codes: training.py ...
user366312's user avatar

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