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Questions tagged [training]

For questions about training networks, rules systems, or other AI system components.

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33 views

Not able to properly tune Neural Network via Back Propagation properly

I have a custom code Neural Network(not using keras or any package...Trying to learn the essence of Neural Network from scratch)... Code can be found here I have the per iteration training output(<...
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0answers
19 views

Train detector : 300 images with 30 objects or 9000 images with one?

so I have this dataset of images of people sitting in a restaurant. I've annotated about 300 images with an average of 30 instances of "person" per image. Now I'm wondering if I should have annotated ...
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1answer
21 views

Model Performance and Size of Data Set

Suppose we have a data set with $4,000$ labeled examples. The outcome variable is trinary (three possible categorical values). Suppose the accuracy of a given model is "bad" (e.g. less than $50 \%$). ...
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0answers
28 views

AI for Warcraft 3 Dota

I want to create AI for Dota1. Is it possible to create AI for Warcraft 3? How Open AI works in Dota2? I want to know more about algorithms what are in foundation in Open AI.
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0answers
20 views

i have trained my model & now trying to predict but unable to do using keras

i have trained my model & now trying to predict but unable to do please help. trying to predict cat or dog stuck in "prediction" ...
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1answer
28 views

Ideal score of a model on training and cross validation data

The question is little bit broad, but I could not find any concrete explanation anywhere, hence decided to ask the experts here. I have trained a classifier model for binary classification task. Now ...
2
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1answer
37 views

How is a neural network where the majority of inputs are 0 trained?

Take alexnet. Alexnet has 1000 output nodes, each of which classify an image: The problem I have been having with training a neural network of similar proportions, is that it does what any reasonable ...
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2answers
2k views

Why L1/L2 regularization technique did not improve my accuracy?

I am training a Multilayer Neural Nets with 146 samples (97 for training set, 20 for validation set and 29 for testing set). I am using: automatic differentiation, SGD method, fixed learning rate + ...
1
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1answer
117 views

How to perform PCA in the validation/test set?

I was using PCA in my whole dataset (and after split to training, validation and test), but after some researchs I found out that is wrong way to do. Then I have few questions: -Are there some ...
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0answers
17 views

Is a Q&A web application content good to be used to train a closed domain chat-bot?

Background I am currently trying to implement Stack Overflow for Teams where I work and this should cover Q & As about various topics from administrative / HR to internal programming questions. ...
3
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0answers
75 views

How can I incrementally train a Yolo model without catastrophic forgetting?

I have successfully trained a Yolo model to recognize k classes. Now I want to train by adding k+1 class to the pre-trained weights (k classes) without forgetting previous k classes. Ideally, I want ...
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4answers
3k views

How do I choose the optimal batch size?

Batch size is a term used in machine learning and refers to the number of training examples utilised in one iteration. The batch size can be one of three options: batch mode: where the batch ...
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0answers
33 views

What to look for when CNN returns same prediction for every input?

I am trying to use a CNN to do a regression prediction on some statistical data. The data is time-series data formatted into a 2-D grid. The network I'm using looks like this: ...
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0answers
12 views

Binary annotations on large, heterogenous images

I'm working on a deep learning project and have encountered a problem. The images that I'm using are very large and extremely detailed. They also contain a huge amount of necessary visual information, ...
7
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5answers
1k views

How can action recognition be achieved?

For example, I would like to train my neural network to recognize the type of actions (e.g. in commercial movies or some real-life videos), so I can "ask" my network in which video or movie (and at ...
0
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1answer
26 views

How to shape the weights or nodes during gradient training of neural network? Training with constraints?

Gradient training changes indiscriminately all the weights and nodes of the neural network. But one can imagine the situations when the training should be shaped, e.g.: One can put constraints on ...
2
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1answer
46 views

Leave One Out Testing

I am currently working with a small dataset of 20x300. Since I have so few datapoints, I was wondering if I could use an approach similar to leave-one-out cross-validation but for testing. Here's ...
3
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1answer
41 views

Decreasing Loss, Constant Accuracy

Problem Statement I've built a classifier to classify a dataset consisting of n samples and four classes of data. To this end, I've used pretrained VGG-19, pretrained Alexnet and even lenet (with ...
1
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1answer
21 views

What is the goal of the model and is the training data relevant to that?

The model that we develop in artificial intelligence.What is its purpose,and what training data is relevant to it.
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2answers
79 views

Drone training, how to train without training data?

I setupped a small drone simulator using PhysX, the time step is at 200 hz, while motors update like regular ESCs (at 50 Hz). I computed the inertia matrix, tweaked a bit mass of components to be real,...
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2answers
190 views

Would AI not obsessed with winning be better citizens of the world?

Some early AI research, inspired by Claude Shannon's maze learning mouse, Theseus, sought to discover resolutions to conflict. In the case of Theseus, the goal was to resolve the conflict between the ...
2
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0answers
38 views

Difference between retraining on different portions of data and training initially on larger data set

I have a large data set that doesn't fit in memory and would have to use something like Keras's model.fit_generator if I would like to train the model on all of the ...
4
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2answers
186 views

Use Machine Learning/Artificial Intelligence to predict next number (n+1) in a given sequence of random increasing integers

The AI must predict the next number in a given sequence of incremental integers (with no obvious pattern) using Python but so far I don't get the intended result! I tried changing the learning rate ...
2
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1answer
28 views

Adding input features - is complete re-training required?

I've never worked with very large models that require weeks or months of training, but in such a situation, what happens if you want to add extra features inputs, do you need to re-train the entire ...
10
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3answers
642 views

Why initial weights in neural network are randomized?

This might sound silly to someone who has plenty of experience with neural networks but it bothers me... I mean randomizing initial weights might give you better results that would be somewhat closer ...
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0answers
18 views

Benefits in using multiple LSTM layers?

I am working on a time series forecasting problem and I am in the process of choosing the optimum network structure. Currently I have a 200 cell LSTM layer fully connected to 100 neurons in an ...
11
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3answers
7k views

How to train a neural network for a round based board game?

I'm wondering how to train a neural network for a round based board game like, tic-tac-toe, chess, risk or any other round based game. Getting the next move by inference seems to be pretty straight ...
2
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1answer
21 views

Is it mostly the case to train with available models

I quite often find projects using pre-trained model and using them as a starting point for their new model that learns something novel from thier dataset or on-live learning process - e.g. using a ...
2
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1answer
30 views

how to benefit from previous training weights in training again to increase accuracy?

I have trained a modified VGG classification CNN, with random initialized weights; therefor the validation accuracy was not high enough for me to accept (around 66%). now using the weights resulted ...
7
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2answers
188 views

What is the machine learning approach based on human learning?

I once came across a neural network being trained without back-propagation or genetic algorithms (or using any kind of data sets). It was based on how the human brain learns and adjusts its ...
0
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1answer
95 views

What is the concept of training a neural network?

I was trying to build an OCR system and heard about ANNs. I am weak at mathematics and statistics and couldn't stick up to reading those massive mathematical documents (research papers or ANN related ...
0
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1answer
34 views

CNN output generally has more than one category in one-hot categorization?

I'm a bit of a CNN newbie, and I'm trying to train one to image classify pictures of pretty similar looking particles. I'm making the inputs and labels by hand from a set of 48x48 grayscale images, ...
3
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1answer
172 views

Why are not validation accuracy and loss as smooth as train accuracy and loss?

I am training a modified VGG16 network for classification (adding 0.5 dropout after each of the last FC layers). In the following plot I am training for a small number of epochs as an example, and it ...
2
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1answer
71 views

Can I calculate the training performance of GPUs by comparing their specification?

I am currently using Nvidia GTX1050 with 640 CUDA cores and 2GB GDDR5 for Deep Neural Network training. I want to buy a new GPU for training, but I am not sure how much performance improvement I can ...
0
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1answer
24 views

Why is a Nvidia Single Board computer less than ideal for AI model training?

Conventional NVIDIA GPUs, such as the Titan and or GT1080, are used to train AI models. Why would a Jetson Nano board be less than ideal as a substitute for a conventional GPU? CONTEXT I would like ...
2
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0answers
28 views

What methods are there to generate artificial training examples based on existing training examples?

I have a small dataset (117 training examples) and many features (4005). Each of the training examples is binary labeled (healthy / diseased). Each feature represents the connectivity between two ...
2
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2answers
59 views

Export trained AI/ML model

From what I know, AI/ML uses a large amount of data to train an algorithm to solve problems. But since it’s an algorithm, I was wondering if it's possible to export it. If I trained an AI with R, ...
1
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0answers
141 views

KnnBasic vs KnnWithMeans

I'm learning a bit about the use of the Surprise library and I have a set of data with users and ratings. I'm training a network with this library, using KNNBasic and KNNWithMeans, this last algorithm ...
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0answers
28 views

Why validation performance is unstable for my LSTM based model (labelling problems)?

I have trained a recurrent neural network based on 1 stack of LSTM cells. I use it to solve a classification problem. The RNN cell has 48 hidden states. The output of the last unfolded LSTM cell is ...
0
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0answers
16 views

Consecutive frames can be discarded when training an SSD/YOLO?

Let's say I have a number of videos, and I want to train an SSD/YOLO (or FRCNN) to detect objects. In the case of a large amount of videos, there will be a lot of frames extracted and transferred to ...
0
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0answers
36 views

Is there a RNN that can predict the next substitute in a floorball match?

Floorball is a type of floor hockey. During the game, substitutions can be made. The team is also allowed to change players any time in the game; usually, they change the whole team. Individual ...
3
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0answers
48 views

How to train CNN such it eliminate dependent features and focuses on independent ones?

How we should train a CNN model when training dataset contains only limited number of cases, and the trained model is supposed to predict class (label) for several other cases, which has not seen ...
5
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3answers
1k views

TensorFlow batch learning

I used the example at - https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/5_DataManagement/tensorflow_dataset_api.py - to create my own classification model. I used different ...
1
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1answer
29 views

Neural network with logical hidden layer - how to train it? Is it policy gradient problem? Chaining NNs?

I am doing neural machine translation task from language S to language T via interlingua L. So - there is the structure: ...
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0answers
18 views

Genetic algorithm generation of fuzzy rules with artificial network adjustment of fuzzy probabilities

Are there any working AI system designs or theory to support a system where an artificial network is trained to to adjust fuzzy probabilities and modify the parameters of a genetic algorithm that ...
0
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1answer
153 views

Can gradient descent training be used for nonsmooth loss functions?

I have non-smooth loss function - e.g. loss(x)=min(x, 0.5). Can gradient descent be used for training neural networks with such functions. Can gradient descent be used for fairly general, ...
3
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2answers
119 views

How do biological neurons weights get initialized?

When trying to map artificial neuronal models to biological facts it was not possible to find an answer regarding the biological justification of randomly initializing the weights. Perhaps this is ...
1
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0answers
17 views

Change parameter in Karaboga's code of ABC algorithm

I'm working on a problem and need to use Karaboga's code of the ABC algorithm but I have some questions... Does this formula for calculating a parameter have to be changed: ...
1
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0answers
38 views

Exploration rate decay and training in Q learning

I'm trying to replicate the results of the DeepMind's paper with Breakout included in OpenAI Gym. I wonder how much frames should I keep until I reach the fixed exploration rate. Actually it reaches ...
1
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1answer
24 views

Training by one batch of examples, what does it mean

Say I have a batch of examples, each examples represent a state: ...