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Create 3D Space for your projects – Break through your. Download Free Tech Support Software Here. Software Description:. Compute spatial data for. The pin file is only.Q:
How can I make predictions on a random forest using the same X, Y and Z input files?
I have a dataset with 1000 samples that has 150 attributes and 7 features are to predict a categorical variable.
I am trying to build a random forest to predict the categorical variable so I can apply the predictions on a test dataset. My inputs for this random forest include the same X, Y and Z input files.
I am confused on the most proper way to predict with the same X, Y and Z files in Python and whether Python is efficient enough to do this.
My thought process:
I create a random forest classifier using the same X, Y and Z files:
import sys
# READ DATA INPUTS
X = pd.read_csv(‘/Users/username/Desktop/random_forest.csv’)
Y = pd.read_csv(‘/Users/username/Desktop/dataset_for_prediction.csv’)
# READ CSV FILES
Z = pd.read_csv(‘/Users/username/Desktop/chunks.csv’)
# NEW INPUT DATA TO THE CLASSIFER
# Use the variables in X, Y and Z dataframes
# and create 3 column vectors of X, Y and Z features
# and add them to the `Input` object
X_new, Y_new, Z_new = x.X, x.Y, x.Z
# CREATE CLASSIFER
classifier = RandomForestClassifier(n_estimators=100, max_depth=10, num
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