All Questions
Tagged with machine-learning linear-regression
263
questions
0
votes
0
answers
34
views
1
vote
1
answer
19
views
Optimize coefficients for multi variable linear regression of scoring metric
I have ecommerce site which I try to optimize my search results to give the most relevant ones for the user.
To give the most relevant results for searches I made a ...
- 111
0
votes
0
answers
10
views
Cost Function Increases, Then Stops Growing
I understand the zig-zag nature of the cost function when applying gradient descent, but what bothers me is that the cost started out at a low 300 only to increase to 1600 in the end.
The cost ...
0
votes
0
answers
23
views
Machine learning model that takes multiple records as input to help predict the last
I want to create a ML model that is able to forecast the yield from a farm. My data source gives me data about the inspections from the field, but that is too much info to fit in 1 record, so there ...
- 1
0
votes
0
answers
22
views
ML Methods For Modelling Latent Variables
I have some time series predictor variables, $\{\mathbf{X}_t\} = \{\mathbf{X}_0, \ldots, \mathbf{X}_n\}$, and some other time series data $\{\mathbf{Z}_t\} = \{\mathbf{Z}_0, \ldots, \mathbf{Z}_n\}$.
...
- 101
1
vote
1
answer
143
views
pos_label=1 is not a valid label. Should be one of [2,4]
I am trying to retrieve my precision score but I am getting an error as follows:
pos_label=1 is not a valid label. It should be one of [2 ,4]
And here is the code ...
- 13
0
votes
1
answer
96
views
Effect on regression coefficients by multiplying a constant to a feature
I was solving one quiz question on Coursera and I found an interesting question.
If you double the value of a given feature (i.e. a specific column of
the feature matrix), what happens to the least-...
- 165
0
votes
0
answers
34
views
Target variable is discrete ranging from 1 to 14, with each value having same proportion in the dataset, ML models fail miserably
I have a dataset of shape (55314,23). The target variable is league_rank. There are exactly 3951 leagues in this dataset, with each club having a ranking from 1 to 14. The variable is discrete, and ...
- 1
1
vote
0
answers
32
views
With infinite observations, would the weights resulting from ridge regression be the same as simple linear regression?
As the number of observations approaches infinity, do the weights of a linear regression approach the weights of a linear regression with L2 penalty?
- 111
0
votes
2
answers
561
views
Why is it difficult to use a linear regression model for the classification problems?
Why is it difficult to use a linear regression model for the classification problems?
user155516
0
votes
0
answers
61
views
Data Cleanup for Regression
I have a simple dataset of 1 output and 1 input and want to fit a linear regression to the dataset.
The data has a certain level of noise to it (potentially driven by another input, which I will ...
2
votes
2
answers
689
views
Parameter estimation in linear regression
Another test Q I couldn't answer -
We have marks of students belonging to 3 sections - A,B,C and two genders - M & F. Which regression model will not be able to estimate all the parameters?
1 ) ...
- 197
0
votes
0
answers
81
views
A hypercube with side length 1 in d dimensions is defined to be the set of points
The Question: A hypercube with side length 1 in d dimensions is defined to be the set of points (x1, x2, ..., xd) such that for all j = 1, 2, ..., d. The boundary of the hypercube is defined to be ...
0
votes
2
answers
83
views
Does LinearRegression uses Gradient Descent for finding slope and y-intercept of the best fit line?
I know that Gradient Descent is an optimization algorithm used for optimizing the cost of the loss function.
Does Linear Regression model of the sklearn package use ...
0
votes
0
answers
29
views
How do you appropriately measure the real mean squared error of a box cox transformed linear regression model?
My understanding is that it can make sense to transform the outcomes of a linear regression model to make them more normally distributed. That's because it could 1) help me find more linear ...
- 101