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Questions tagged [regression]

For questions related to regression (both linear and non-linear) in the context of machine learning and AI.

2 votes
1 answer
118 views

For any given learning task, if I know the nature of dependence to be learnt, how to select the width and depth of the neural network? How does the number of ground truths affect this? Let's say I ...
Sameer Kulkarni's user avatar
0 votes
2 answers
79 views

I am using a machine learning model to remove interference from range-doppler maps to detect targets. I am using a supervised approach, in which I give as input the range-doppler map of target+...
ThinkPad's user avatar
2 votes
1 answer
67 views

I am working on a project to forecast food sales for a corporate restaurant. Sales are heavily influenced by the number of guests per day, along with other factors like seasonality, weather conditions,...
Mashu's user avatar
  • 21
0 votes
0 answers
45 views

I'm trying to approximate the following analytic function with 5 input variables ($x_i\in(0,5),\ i\in\{0,...,4\}$). The output variable $y$ is continuous. ...
c6m38's user avatar
  • 1
1 vote
1 answer
107 views

I am training Deep Learning models to predict the Remaining Useful Life (RUL) of certain devices. The RUL is an estimate of the time remaining until the device is expected to fail. Accurate ...
user386164's user avatar
0 votes
0 answers
111 views

I'm working on a project where I need my model to predict a sequence of n 3x3 matrices given an input sequence of n 3x3 matrices ...
Awwab Azam's user avatar
1 vote
1 answer
101 views

I have the following task to do: I have time series data. Training by the consecutive 3 days to predict the each 4th day. Each day data represents one CSV file which has dimension 24x25. Every ...
S. M.'s user avatar
  • 123
1 vote
1 answer
108 views

My dataset is around 100k rows and is tabular data. My question is this: Is there a case to use deep learning here? My current approach is the following: 1) training a supervised on historical data ...
Burger's user avatar
  • 13
0 votes
0 answers
19 views

I'm building an AI model using Google's 'Civil-Comments' dataset. It has 7 different labels, each a float than can be anywhere from 0 to 1. Embedding Bags, which I have read about. do not perform well....
ShadowProgrammer's user avatar
0 votes
0 answers
61 views

I can use any machine learning algorithms (but neural networks are better for me) to resolve this issue: use few elements as input (numerical) to predict more elements as output. In normal regression ...
Cyr's user avatar
  • 101
0 votes
1 answer
62 views

I am fairly new to TensorFlow and ML in general and am currently working on a regression neural network while learning about different parts and concepts of it. My goal is to try & achieve a model ...
tomazj's user avatar
  • 101
0 votes
1 answer
120 views

Lets say we have an arbitrarily large stream of numbers, numbers ranging from 1 to 100. You know these numbers follow a known distribution, e.g exponential distribution. Is it possible predict the ...
Luk's user avatar
  • 11
0 votes
1 answer
78 views

I am working on a regression task where the model has to predict two values at the same time. The idea is that the dataset consists of 16 features, where the first 8 features represent the first value ...
lukachu03's user avatar
0 votes
0 answers
63 views

Attached image. How would you find the relationship between independent variable (x) and dependent variable (y)? Is it linear or non-linear? What would the function looks like? P.S. I believe this is ...
DLCVIP007's user avatar
0 votes
1 answer
83 views

I've been playing around with some behavioral cloning of a simple old game that uses a joystick. As with behavioral cloning in general, if I record many games, then for each state there are many ...
eof's user avatar
  • 121

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