Stack Overflow Asked by himanshu040 on February 19, 2021
I am trying to do the machine learning practice problem of Heart disease , dataset from kaggle.
Then i tried to split data into train set and test set and after that combing models into single function and predicting,this error shows up in jupyter notebook .
Here’s my code:
# Split data into X and y
X = df.drop("target", axis=1)
y = df["target"]
Spliting
# Split data into train and test sets
np.random.seed(42)
# Split into train & test set
X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.2)
Prediction function
# Put models in a dictionary
models = {"Logistic Regression": LogisticRegression(),
"KNN": KNeighborsClassifier(),
"Random Forest": RandomForestClassifier()}
# Create a function to fit and score models
def fit_and_score(models, X_train, X_test, y_train, y_test):
"""
Fits and evaluates given machine learning models.
models : a dict of differetn Scikit-Learn machine learning models
X_train : training data (no labels)
X_test : testing data (no labels)
y_train : training labels
y_test : test labels
"""
# Set random seed
np.random.seed(42)
# Make a dictionary to keep model scores
model_scores = {}
# Loop through models
for name, model in models.items():
# Fit the model to the data
model.fit(X_train, y_train)
# Evaluate the model and append its score to model_scores
model_scores[name] = model.score(X_test, y_test)
return model_scores
And when i run this code , that error shows up
model_scores = fit_and_score(models=models,
X_train=X_train,
X_test=X_test,
y_train=y_train,
y_test=y_test)
model_scores
Your X_train
, y_train
, or both, seem to have entries that are not float numbers.
At some point in the code, try using
X_train = X_train.astype(float)
y_train = y_train.astype(float)
X_test = X_test.astype(float)
y_test = y_test.astype(float)
Either this will work and the error will go away, or one of the conversions will fail, at which point you will need to decide how (or if) you want to encode the data as a float.
Answered by Ami Tavory on February 19, 2021
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