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We currently have an example of a loss function for regression models. Specifically, we implement the root mean squared error.
However, we don't currently have an example of a loss function for cla…
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It would be great to be able to use Econometrics.jl models in MLJ.
In particular, I would really like to see the Econometrics.jl multinomial logistic regression model available in MLJ.
cc: @Nosf…
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The description of fit_multinom_dag() says that given the structure of a Bayesian network it estimates the parameters using multinomial logistic regression. Is this the function used to find inference…
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I use the logistic regression classifier(LogisticRegression(multi_class="multinomial", solver="newton-cg", max_iter=1000)) for classification, which cannot achieve the effect of the paper. Would you l…
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hi, in your example for neural-network.py, the function neural_net, layer_1 = tf.layers.dense(x, n_hidden_1) is without activation, in my opinion, this example is equal with a multinomial logistic reg…
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Maybe I have missed it in the library, but is there a way to use frequency weights for multinomial logistic regression? If not, I would like to request it.
**edit** question is for fractional or c…
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(just an idea, while thinking about beta regression)
zero and one inflate beta regression (there is some literature that I didn't look at.)
continuous part can be estimated from truncated sample, …
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I have been using `tbl_regression()` to produce tables displaying `multinom()` outputs. However I need to weight my analysis and have been using `svymultinom()` (from `CMAverse`: https://github.com/BS…
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**Fundamentals**
1. Introduction to ML
- What is ML
- Types of ML systems
- ML in R
2. Before the modeling process
- Problem framing
- Planning & scoping
- Experimentation
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Hi,
I've been trying to plot marginal effects for a multinomial regression model. I tried using the `mnl_pred_ova` function, but I have several factor (binary) independent variables which the functio…