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Questions tagged [machine-learning]

For questions about machine learning (ml) and the related concepts with respect to AI.

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Can't get the right shape for tf.squared_difference

My train data has a shape X_train.shape is (111453, 400, 5) and Y_train.shape is (111453,1) I have 3 layers and the output layer ...
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11 views

How to train a model by accounting for boundary constraints?

I've a robot traverse through a grid layout. Based on the wheel speed difference I classify actions as either straight, left or right. I computed the distances based on the time duration and the speed ...
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Which pretrained embeddings version to choose ?

I want to use pretrained embeddings. Let's say FastText. But from the website, there is several versions available : Pre-trained word vectors learned on different sources can be downloaded below: ...
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9 views

Machine learning for presser sensor via Accord.Net

0 down vote favorite Our system has 4 pressure sensors and they give us data each 10 seconds and we use it to claculate average presser in the sistem. So basically we have table like Timestamp - ...
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8 views

Usefulness of Data augmentation for non-overfitting network [NLP]

(Maybe related : Usefulness of Dropout for non-overfitting network) My neural network does not overfit. Using Data augmentation in a non-overfitting network can increase its accuracy ? Note : I'm ...
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15 views

Detect root cause across many event occurrences

Suppose there are sensors which supply numerical metrics. If a metric goes above or below healthy threshold, an event (alert) is raised. Metrics depend on each other in one way or another (we can ...
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3answers
30 views

Batch mode vs mini-batch mode vs stochastic mode

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 ...
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0answers
10 views

How exactly is equivariance achieved in capsule networks?

I have read quite a lot about capsule networks but cannot understand how the squashed vector would also rotate in response to rotation or translation of the image.A simple example would be helpful.I ...
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1answer
22 views

Does overfitting imply an upper bound on model size/complexity?

Suppose that I have a model M that overfits a large dataset S such that the test error is 30%. Does that mean that there will always exist a model that is smaller and less complex than M that will ...
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23 views

First perceptron learning algorithm

I struggle to find Rosenblatts perceptron training algorithm in any of his publications from 1967 - 1951, namely: [1] Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms [2] ...
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1answer
23 views

How to perform neural network with output constraint?

Imagine a "simple" feedforward, fully connected neural network, with some input size, some number of hidden layers, and some # of neurons....etc BUT with a fixed number of output size (that is saying, ...
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1answer
19 views

Usefulness of Dropout for non-overfitting network

My neural network is simple enough and does not overfit. Dropout is a regularization technique for reducing overfitting in neural networks From Wikipedia Adding Dropout in a non-overfitting ...
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1answer
12 views

Neural Network for OMR?

I've created a neural net using the ConvNetSharp library which has 3 fully connected hidden layers. The first having 35 neurons and the other two having 25 neurons each, each layer with a ReLU layer ...
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0answers
10 views

What is the most common way \delta is defined as (in the context of a neural network)

Two highly reliable sources: Brilliant defines \delta as such: https://brilliant.org/wiki/backpropagation/ Meanwhile Nielsen defines it as such: http://neuralnetworksanddeeplearning.com/chap2.html ...
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22 views

Simple feed-forward nn does not learn

dataset can be retrieved here: https://www.kaggle.com/uciml/pima-indians-diabetes-database/downloads/diabetes.csv/1 ...
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0answers
17 views

How to use Machine Learning to create a “Draw-A-Person Test”

The process revolves around a child's drawing. Each part of each drawing corresponds to a score as in the Draw a Person Test conceived by Dr. Florence Goodenough in 1926. The goal of the machine is to ...
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1answer
18 views

Why is there Transition layers in DenseNet?

The DenseNet architecture can be summarize with this figure : Why there is transition layers between each blocks ? In the papers, they justify the use of transition layers as follow : The ...
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2answers
45 views

How to improve testing accuracy when training accuracy is high?

Following-up my question about my over-fitting network My deep neural network is over-fitting : I have tried several things : Simplify the architecture Apply more (and more !) Dropout Data ...
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1answer
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35 views

Can AI 'fix' heavily compessed videos/photos?

So let's say you had a really nice day in a flight simulator and you are getting videos of this type of quality: This is Full HD (1080p), but heavily compressed. You can literally see the pixels. Now ...
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2answers
55 views

Decision making systems applications

Machine learning and data science are mainly made for processing large amounts of data nowadays, for example - a multitude of pictures. But do these fields have some applications in the decision ...
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2answers
36 views

What models is Google's quick draw using?

Quick draw is a Google experiment using user generated online doodles and machine learning to play a game of "Guess what I'm drawing" similar to the board game Pictionary. I'm interested if anyone ...
2
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1answer
33 views

How to find the category of a technical text on a surface-semantic-level

There are some predefined categories( Overview, Data Architecture,Technical Details, Applications etc). The requirement is to classify the input text of paragraphs into their resp. category. I cant ...
2
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1answer
31 views

Should the reward or the Q value be clipped for reinforcement learning

When extending reinforcement learning to the continuous states, continuous action case, we must use function approximators (linear or non-linear) to approximate the Q-value. It is well known that non-...
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1answer
42 views

Interpretation of a good overfitting score

As shown below, my deep neural network is overfitting : where the blue lines is the metrics obtained with training set and red lines with validation set Is there anything I can infer from the fact ...
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0answers
8 views

Pre priming a network for white space

When a human looks at a page. He notices the sets of letters are grouped together separated by white space. If the white space was replaced by another character say z, it would be harder to ...
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0answers
37 views

Reinforcement learning for segmenting the robot path to reflect the true distances

I've a grid of rectangles acting as blocks. The robot traverses through the inter-spaces between these consecutive blocks. Now I have sensor data streaming in representing Right and left wheel speeds. ...
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1answer
27 views

In apprenticeship learning, is it possible to outperform the master?

As stated in the title, I'm wondering if it would be possible to "outperform" the master in the apprenticeship learning. I'm aware that the question might be not clear enough; but hopefully, someone ...
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3answers
45 views

How to detect a Neural Network will work with the whole dataset?

I want to implement a neural network on a big dataset. But training time is long (~1h30 per epoch). I'm still in the development process, so I don't want to wait such long time just to have poor ...
3
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1answer
57 views

Why do you not see dropout layers on reinforcement learning examples?

I've been looking at reinforcement learning, and specifically playing around with creating my own environments to use with the OpenAI Gym AI. I am using agents from the stable_baselines project to ...
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0answers
15 views

How to create Partially Connected NNs with prespecified connections using Tensorflow?

I'd like to implement a partially connected neural network with ~3-4 hidden layers (a sparse deep neural network?) where I can specify which node connects to which node from the previous/next layer. ...
2
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1answer
19 views

Dealing with Lags in Reinforcement Learning

Following up on my previous questions using a hypothetical AI system to manage air flow using dampers to achieve an optimal target of exactly equal airflow at a number of vents; (thank you for all ...
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2answers
149 views

Is known math really enough for AI

As an Electronics & Communication Engineering student I've heard some stories and theories about "The math we have is not enough to complete a thinker-learner AI." What is the truth? Is humankind ...
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3answers
197 views

What is the name of an AI system that learns by trial and error?

Imagine a system that controls dampers in a complex vent system that has an objective to perfectly equalize the output from each vent. The system has sensors for damper position, flow at various ...
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0answers
20 views

How does using neural network to improve evaluation function work?

I’ve seen some papers using neural network as evaluation function to evaluate game state. I wonder if they can value the state to train the neural network, isn’t the function that is used to value the ...
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0answers
28 views

Autoencoder why it is special for image decoding?

I have read about auto encoder. Understood what is encoding part, and decoding part, and the latent space. Now, i tried to implement this in keras. Below is the code. ...
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1answer
35 views

Python API for publicly available datasets

In my daily machine learning / deep learning workflow, I often want to interact with a dataset in my code. Specifically, I would like to be able to load some module / package which can make sure that ...
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28 views
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1answer
48 views

How to find partial derivative of softmax w.r.t logits in python

i have trouble implementing back propogation for multi class classification of CIFAR10 dataset My neural network has 2 layers forward propagation X -> L1 -> L2 weights W are initialized as random ...
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1answer
253 views

Loss jumps abruptly when I decay the learning rate with Adam optimizer in PyTorch

I'm training an auto-encoder network with Adam optimizer (with amsgrad=True) and ...
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1answer
68 views

Machine learning to predict 8*8 matrix values using three independent matrices

Problem Statement I have 4 main input features. This is a small snippet of the data for clearer understanding. Gate name -> for example AND Gate index_1 -> ...
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0answers
25 views

Mapping Actions to the Output Layer in Keras Model for a Board Game

I have created a game based on this game here. I am attempting to use Deep Q Learning to do this, and this is my first foray into Neural networks (please be gentle!!) I am trying to create a NN that ...
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0answers
12 views

How to handle Feature changes in a model deployed ?

I implemented and deployed with Flask an XGBoost model for a classification problem. But being aware that features importance can change over time to predict probability of label for new data, I ...
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0answers
13 views

Different results when using PCA and Kernel-PCA with a linear kernel in sklearn

I have been trying to reduce the dimensionality of my dataset using kernel-PCA from scikit. However, I did a small experiment trying to use the linear kernel in kernel-PCA and the regular PCA model. ...
3
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1answer
44 views

Does balancing the training data set distribution for a neural network affect its understanding of the original distribution of data?

I have a very imbalanced dataset of two classes: 2% for the first class and 98% for the second. Such imbalance does not make training easy and so balancing the data set by undersampling class 2 seemed ...
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1answer
30 views

What is the approach to deduce formal rules based on data?

We have data in text format as sentences. The goal is to detect rules which exist in this set of sentences. I have a limited set of contextless sentences that fit a pattern and want to find the ...
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0answers
20 views

Convolutional Layers on a hexagonal grid in Keras

Keras' convolutional and deconvolutional layers are designed for square grids. Is there was a way to adapt them for use in hexagonal grids? For example, if we were using axial coordinates, the input ...
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1answer
59 views

Resources for learning Machine Learning

So I have already learned some traditional AI techniques (alpha-beta pruning, MCTS). Now I want to get into Machine Learning. I know a little bit about neural networks, but that is about it. What are ...
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1answer
39 views

Should I use Monte Carlo or a classifier for this Decision Making problem?

I want to build a model to support decision making for loan insurance proposal. There are three actors in the problem: a bank, a loaner applicant (someone who ask for a loan) and a counselor. The ...
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2answers
112 views

AlphaZero Value Network

The Alpha Zero (as well as AlphaGo Zero) papers say they trained the value head of the network by "minimizing the error between the predicted winner and the game winner" throughout its many self play ...