Younes-Charfaoui

# import the libraries
from sklearn.neighbors import LocalOutlierFactor
import pandas as pd

# read your data
data = pd.read_csv("yourData.csv")

# create the isolation forest
outlier_detection = LocalOutlierFactor()

Younes-Charfaoui

# import the libraries
from sklearn.cluster import DBSCAN
import pandas as pd

# read your data
data = pd.read_csv("yourData.csv")

# create the isolation forest
outlier_detection = DBSCAN(eps = 0.2, metric=”euclidean”, min_samples = 5, n_jobs = -1)

Younes-Charfaoui

# import the libraries
from sklearn.ensemble import IsolationForest
import pandas as pd

# read your data
data = pd.read_csv("yourData.csv")

# create the isolation forest
outlier_detection = IsolationForest()

Younes-Charfaoui

# import the KNN imputer
from sklearn.impute import KNNImputer

# create the imputer with specefied number of neighbors (the K)
imputer = KNNImputer(n_neighbors=3)

# fit the imputer to the train set
imputer.fit(train)

# transform the data

Younes-Charfaoui

# This estimator is still experimental, we need to explicitly require this experimental feature.
from sklearn.experimental import enable_iterative_imputer 
from sklearn.impute import IterativeImputer

# create the imputer
imputer = IterativeImputer(random_state=22)

# fit the imputer to the train set
imputer.fit(train)

Younes-Charfaoui

# import the pandas and James Stein encoders libraries.
import pandas as pd
from category_encoders import JamesSteinEncoder

# get you data.
data = pd.read_csv("yourData.csv")

# create the encoder.
encoder = JamesSteinEncoder(return_df=True)

Younes-Charfaoui

# import the pandas and Leave One Out encoders libraries.
import pandas as pd
from category_encoders import LeaveOneOutEncoder

# get you data.
data = pd.read_csv("yourData.csv")

# create the encoder.
encoder = LeaveOneOutEncoder(return_df=True)

Younes-Charfaoui

# import the pandas and catboost encoders libraries.
import pandas as pd
from category_encoders import CatBoostEncoder

# get you data.
data = pd.read_csv("yourData.csv")

# create the encoder.
encoder = CatBoostEncoder(return_df=True)

Younes-Charfaoui

private fun stopActivityRecogntion() {
    
    LocalBroadcastManager.getInstance(this).unregisterReceiver(receiver)
    
    ActivityRecognition.getClient(this)
        .removeActivityTransitionUpdates(pendingIntent)
        .addOnSuccessListener {
            Log.d("ActivityRecognition", "ActivityTransitions successfully unregistered.")
        }
        .addOnFailureListener { e ->

Younes-Charfaoui

// creating the pending intent
val intent = Intent(DetectedActivityReceiver.RECEIVER_ACTION)
pendingIntent = PendingIntent.getBroadcast(this, 0, intent, 0)

// creating the receiver
receiver = DetectedActivityReceiver()

// registring the receiver
LocalBroadcastManager.getInstance(this).registerReceiver(
    receiver, IntentFilter(DetectedActivityReceiverRECEIVER_ACTION)