Hyperopt is a Python library for serial and parallel optimization over awkward search spaces, which may include real-valued, discrete, and conditional dimensions
Questions tagged [hyperopt]
128 questions
0
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Errors with mlflow and machine learning project using XGBoost and hyperopt in python
I'm experiencing some problems with a machine learning project.
I use XGBoost for forecast on warehouse items supply and i'm trying to select the best hyperparams with hyperopt and mlflow.
This is the code:
import pandas as pd
import glob
import…
calabrone
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0 answers
FreqTrade not taking a position: No params for buy found, using default values
My freqtrade bot wont take a position. Locally, I have no problems running or backtesting but, when running the Docker image in the cloud, it does not take a position. It has been running in the cloud for nearly 48hrs. I see indicators on my graph…
Doing Things Occasionally
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Hyperopt best param score interpretation and usage
Have a question regarding the Hyperopt Score output and best param output. After running the best_param (as shown in the example), it generated best loss: -0.0921409214092141 with the final score being 0.06775067750677506. However, when I used the…
ManOnTheMoon
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Positional arguments for HyperOpt fmin() function
I am trying to user hyperopt.fmin to optimize the hyperparameters of a XGBoost classifier. I have an objection function:
from hyperopt import fmin
def objective(space, x1, x2):
'do whatever to define loss_array'
return {'loss':…
deblue
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1 answer
Error while hyper parameter tuning of XGBRegressor in xgboost
I have been trying tune my XGBoost model in order to predict values of a target column, using the xgboost and hyperopt library in python. After importing the required libraries correctly, the domain space, objective function and running the…
Shrinidhi Narasimhan
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How to run Adaptive TPE in hyperopt?
I read documentation of Hyperopt in python, and I found, that there are three possible methods:
RandomSearch
TPE
Adaptive TPE
To run random search we have command rand.suggest, and TPE tpe.suggest, however, I couldn't nowhere find any command…
John
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randint(low=4, high=12) returns a number lower than 4
I am using using Hyperopt's randint in one of my hyperparameter tuning experiments, where my model is getting hyperparamter values from fmin that are lower than than the lower limit specified for randint,
I am passing the following parameters to the…
Prateek Singh
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1 answer
Running Hyperopt in Freqtrade and getting crazy results
I ran hyperopt for 5000 iterations and got the following results:
2022-01-10 19:38:31,370 - freqtrade.optimize.hyperopt - INFO - Best result:
1101 trades. Avg profit 0.23%. Total profit 25.48064438 BTC (254.5519Σ%). Avg duration 888.1 mins.
with…
Pruthvi
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How to search a set of normally distributed parameters using optuna?
I'm trying to optimize a custom model (no fancy ML whatsoever) that has 13 parameters, 12 of which I know to be normally distributed. I've gotten decent results using the hyperopt library:
space = {
'B1': hp.normal('B1', B1['mean'], B1['std']),
…
XiB
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Freqtrade 2021.7 Hyperopt space defining issue
I'm new to freqtrade. I want to optimize some parameters in my strategy. As far as I see, with freqtrade 2021 we can optimize parameters without defining a seperate hyperopt file. I have followed the example on…
Patroclos
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0
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Making hyperparameters add up to 1 when fine tuning using Optuna
I have a function which looks like this:
def fine_tuning(x,y,model1,model2,model3,trial):
pred1 = model1.predict(x)
pred2 = model2.predict(x)
pred3 = model3.predict(x)
h1 = trial.suggest_float('h1', 0.0001, 1, log = True)
h2 =…
jr123456jr987654321
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1 answer
How to use mlrMBO with mlr for hyperparameter optimisation and tuning
Im trying to train ML algorithms (rf, adaboost, xgboost) in R on a dataset where the target is multiclass classification. For hyperparameter tuning I use the MLR package.
My goal of the code below is to tune the parameters mtry and nodesize, but…
nelepi
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Setting task slots with pyspark on an individual machine
I am trying to run the optimization of a ML model using SparkTrials from the hyperopt library. I am running this on a single machine with 16 cores but when I run the following code which sets the number of cores to 8 I get a warning that seems to…
user2287387
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How to install HyperOpt-Sklearn library in Google Collab?
Every time I try to install HyperOpt-Sklearn library in Google Collab, I get the following error:
fatal: destination path 'hyperopt-sklearn' already exists and is not an empty directory.
/bin/bash: line 0: cd: hyperopt: No such file or…
LD-DS-00
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1 answer
To optimize 20 parameters which should be the best algorithm to use?
I have 20 parameters that can take binary value which are passed to function to return the score like this.
score = fmin( para 1, para 2 , para 3,.....para20)
Now to optimize this scenario, which can be the best algorithm ?
I read about genetic…
Ishan Kumar
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