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Questions tagged [h2o]

H2O is an in-memory platform for distributed, scalable machine learning.

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6 views

What kind of impact do autoencoders have on final model performance when compared to models trained only on supervised data?

For example, say we have two datasets, a labeled set (I will call it df_labeled) of nrows=200k and an unlabeled dataset (df_unlabeled) of nrows=800k and we want to build a binary classifier. I clearly,...
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1answer
17 views

Quadratic Weighted Kappa metric in H2O package for model performance

I am running a multiclassification problem and before I make a function by myself I was wondering if anyone knows of a pre built quadratic weighted kappa function in the h2o library.
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0answers
25 views

H2O (open source) for K-mean clustering [closed]

I am using H2O (H2O flow, in particular) to do K-means clustering. I selected "standardize" checkbox which makes sure "It standardize columns before computing distances". It trained fine and I ...
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1answer
22 views

H2o k-fold validation [closed]

I need to get some clarification on how H2o creates a training model from the k-fold validations. Below is my understanding, please correct where I am wrong: If I set nfolds = 5, then H2o will split ...
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1answer
32 views

DeepLearning & Anomaly Detection - Understanding & How to Properly Tune

I'm looking into understanding the Deeplearning anomaly detection algorithm provided by h2o. I tried to recreate an example below. Perhaps some of these questions are basic, but I'm trying to better ...
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0answers
57 views

Training RMSE higher than Validation RMSE in H2O

I am using the H2O-DeepLearning Model for a Regression Problem. What i observe is that Training RMSE is higher than Validation RMSE. I am using the model with default parameter which is two hidden ...
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1answer
84 views

H2O GBM and Caret GBM

Hi I have doubt regarding the interaction. depth parameter in caret. I found a useful link hereabout interaction.depth in caret Now I am trying to find the similar parameter in H2O-GBM . Can anyone ...
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1answer
37 views

categorical_encoding in h2o - what is the difference between the options

I'm trying to understand the pros/cons and when to use the various encoding options that are available to me in h2o with the parameter 'categorical_encoding'. It would be helpful if people could ...
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2answers
56 views

May somebody help with interpretation of trees from h2o.gbm, see as photo attached

This picture is from h2o.gbm, while I'm not sure how to interpret the numbers in it. What is the big title "Class NO" mean? Does it mean the root node is labeled "No"? Or does it mean this tree is ...
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1answer
61 views

Issues with XGBoost on H2O environment

I have a dataset from which I built lags at different levels to use as features in the XGBoost model. When I ran XGBoost models on H2O, the model is picking up the features which contain higher values ...
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1answer
31 views

Is setting a self learning system possible via incremental (online) learning?

Self learning and incremental learning are all new to me. I am trying to develop a system for one of my case. Simply I have a data set (with about 90K observations and 400 features) for a binary ...
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2answers
44 views

How NULLs in numerical variables are treated in tree-based models?

I understand that in tree-based models (CART, Gradient boosted trees, etc.), NULLs (i.e., NaN) in categorical variables can be treated as a separated category, while making node splits. However, how ...
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2answers
42 views

h2o : Any components not running or stored on local machine? [closed]

The descriptive language used when referencing how h2o works is a little confusing to me at times (e.g., client, cluster, "internet"). I try to remain vigilant in not uploading or exposing my datasets ...
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1answer
50 views

Help about cosine simulating in h2o [closed]

So I'm beginning in deep learning and especially in h2o. I tried to simulate cosine function in R, not to compute it like for example by using h2o.cos(), But after many and many more combinations of ...
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0answers
53 views

balance_classes in H2O, but for regression? [closed]

I am training with deep learning for regression in H2O for R. My dataset is unbalanced (ie. not evenly distributed). There has been discussion on whether unbalanced datasets are an issue or not, with ...
4
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1answer
38 views

Special values in continuous numerical variables/features in Random Forest

I have a binary response variable I am seeking to predict using Random Forest. I have a sizable dataset of 150k rows, I have about 200 independent variables or features to use to model the outcome. ...
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1answer
84 views

Extracting H2o Cross Validation Results

I am using H2o library in R and have a slight confusion that you learned people might be able to help with. I am not sure how to interpret the output from ...
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1answer
62 views

H2O PCA number of components

I wonder why number of components in H2o PCA algorithm is limited to 9. It is not sure sometimes to be enough. k: Specify the rank of matrix approximation. This can be a value from 1 to 9 and ...
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0answers
79 views

How to improve GBM performance

I'm trying to model insurance losses, with a Tweedie distribution. I have a data set of about 40 million records, and over 100 independent variables. My response variable is "loss", I take the log of ...
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1answer
309 views

H2o interpretability - LIME

I have trained a model to predict heart attacks using random forest algorithm using H2O. I have good performance in cross validation. Now, I want to give more interpretation to the predictions in a ...
2
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1answer
98 views

How is deviance defined in H2O Deep Learning if the loss function is not quadratic?

One can set the parameter “stopping_metric” to “deviance” for the deeplearning algorithm (http://docs.h2o.ai/h2o/latest-stable/h2o-py/docs/modeling.html#h2o.estimators.deeplearning....
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0answers
26 views

How is the parameter „huber_alpha“ defined in H2O Deep Learning?

In the documentation of the H2O software (http://docs.h2o.ai/h2o/latest-stable/h2o-docs/data-science/deep-learning.html) it says for the parameter “huber_alpha: Specify the desired quantile for Huber/...
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1answer
641 views

H2O AUTOML: How to save, reuse and build on top of existing automl models? [closed]

I have two questions on h2o.automl and I couldn’t find any documentation on these topics. I can save/reuse the leader (automl) model in R using h2o.saveModel and h2o.loadModel. But how do I save/...
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1answer
160 views

feature engineering for auto encoder anomaly detection

I am working on an unsupervised problem: to take a set of transactional data, and identify anomalous transactions. I am using h2o's auto encoder to train a model which then scores transactions based ...
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0answers
38 views

“beta_given” column in the h2o.glm beta_constraints

What does the "beta_given" column do in the h2o.glm beta_constraints parameter? h2o is an open source library for machine learning algorithms. There are several online examples on how to install the ...
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1answer
32 views

Difference in parameters between grid summary and individual models

I was using h2o for getting a feel of what learning rate does a good job on my data set. I chose to use cross validation for selecting a learning rate. ...
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0answers
1k views

Implementing “Balanced Random Forest” in h2o

Currently having problems with (very) imbalanced classes in a dataset that I am trying to run binary classification on. Looking at this UC Berkeley article (http://statistics.berkeley.edu/sites/...
1
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1answer
120 views

Reduce over-forecasting in H2O regression with tree-based algorithms

I'm trying to solve a time series forecasting problem. While accuracy is fine, I'm now trying to punish / reduce under-forecasting events where the forecast is too low. Forecasting approach: Build ...
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1answer
626 views

Training threshold vs validation threshold for better prediction results?

Between the two, should I use a model's training or validation threshold to get best results (from a distributed random forest binary classifier built using h2o.ai) ...
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2answers
219 views

Deviances in H2O

does anyone know how exactly the Deviances (Poisson, Gamma, Tweedie) are computed in H2O? I cannot find the functions. For interpretation purposes I would like to know the calculations. Thank you!
4
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1answer
534 views

Regularized GLM with aggregated data

I am fitting a poisson GLM to model claim rates. Since I have 1.5m+ records, I have aggregated my data (to improve efficiency). My understanding is that using aggregated data with a poisson GLM will ...
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1answer
144 views

Which algorithm is used for the H2O AutoML metalearner [closed]

We know that h2o.automl() uses GBMs, Random Forest, DNNs, GLMs, and Extremely-Randomized Forest as base-learners, but what algorithm is used as the metalearner to ...
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1answer
597 views

Can we force monotonicity for a subset of features in h2o gbms?

I was wondering if it's possible to force variables to be monotonic when building gbms in h2o? Ideally this would be enforced globally, although even the standard local constraint would be better than ...
2
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1answer
213 views

Is polynomial regression possible in H2O? [closed]

Is there a way to carry out polynomial regression $x + x^2$ in H2O (Python)? What I have found about this is "interactions" option in GLM. However, I am not sure if this option yields polynomial ...
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2answers
506 views

can I use h2o or mxnet to do time series prediction?

I have a time series like 4, 6, 10, 12, 2, 23, 4,... It is not a stationary time series so I do not want to use arima algorithm. I perfer neural networks. There is some algorithm in R package such as ...
2
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1answer
375 views

Random Forest cross-validation r2 is high but predictions on simulated data are bad

I have a dataset with 46 million observations and 25 predictors. I am training my model in the python h2o package like so: ...
2
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2answers
216 views

How are the epochs and iterations defined in a h2o deep learning perspective?

As per the usual definition of epoch and iteration, it takes multiple iterations to complete 1 epoch (for example see https://stackoverflow.com/questions/4752626/epoch-vs-iteration-when-training-...
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1answer
284 views

Use of previously set cross validation set for ensemble models in h2o

I have time series dataset and as a requirement I prepare a 10 fold cross validation dataset. Briefly, I split data into 10 and for each training set I put a gap between last, first day of validation ...
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2answers
2k views

Random forest variable importance in h2o (classification problem)

I cannot find out how the variable importance for classification problems is calculated in h2o. There is a Stackoverflow question asking the same, but the accepted ...
2
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1answer
375 views

How to map values reconstructed with a deep learning autoencoder back to categories

My colleague and I are working on a dataset full of categorical variables using an deep learning model with autoencoder of H2O package in ...
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0answers
181 views

Splitting criteria based on MSE in H2O DRF (Random Forest) and GBM

Why do H2O Random Forest and GBM implementation use MSE (mean squared error) for node splitting metric? As I understand from the H2O docs, no matter the response column is factor or numeric, the tree ...
1
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1answer
467 views

L1/L2 Generalization with value setting 0 in H2O

I'm am using the h2o.deeplearning() function in R, and in the parameter setting, there is l1 and l2. The documentation for L1/L2 regularization says: L1 ...
2
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1answer
122 views

Fractional epoch in deep learning using H2O

I understand the concept of epoch as epoch = one forward pass and one backward pass of all the training examples, in the neural network terminology. So i assume it must be an integer, however why in ...
4
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1answer
228 views

use of sample_rate = 1 in randomForest - to fit a single tree [closed]

I would like to fit a single tree. In the h2o R package, I can use h2o.randomForest() with the following options: ...
3
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1answer
1k views

With H2O AutoML is it okay to use my test set as the leaderboard?

Normally in machine learning we will split our data into train, valid and test. The valid data is used to tune the parameters, and the test data is then used to check the performance of our best tuned ...
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2answers
339 views

machine learning model true negative rate is too low while true positive rate is too high

I am using the tm package and h2o package to do text mining using neural network. Here I have a data frame of 100 most frequent words in the text. These variables only have values of non-negative ...
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1answer
220 views

Sudden increase in log-loss on training set with H2O GBM

I am performing a hyperparameter grid search for a GBM classifier in H2O, running version 3.10.4.8 (on top of python 3.5.3). This is a multiclass problem (~40 classes). As a first test, I tried a ...
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1answer
460 views

Why is my predicted vs observed plot worse for training than validation. Running an overfitted GBM on a binomial outcome

I have a binomial outcome that I am trying to predict using a gbm in h2o. I have set quite a low min_rows value for each node and it appears to be overfitting. See plots below. When I group the ...
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2answers
3k views

H2O: Can I use the h2o for time series predictions?

I understand that there is not a specific model for time series modeling in H2O. Is there a workaround in order to use Deep Learning or/and GBM? Is some kind of data transformation necessary? are ...
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1answer
142 views

Neural Network and H2O.ai: inputs that have multiple right answers (questions about a previously answered question)

I have two questions related to this previously answered question. Can someone explain how the NN's backproagation algorithm would not be able to function properly when inputs have multiple right ...