<jupyter_start><jupyter_text>Project - Parameters with Highest Impact on House Price Class ![Data Science Workflow](img/ds-workflow.png)  Goal of Project- The real estate dealer from last assignment calls back and clarifies his objective- Not so interested in finding what matters most to find house price, but more in which range a house is in.- There are 3 classes: 33% cheapest, 33% mid-range, 33% expensive houses.- He needs to find which 10 parameters matters most to determine that  Step 1: Acquire- Explore problem- Identify data- Import data  Step 1.a: Import libraries- Execute the cell below (SHIFT + ENTER)- NOTE: You might need to install mlxtend, if so, run the following in a cell```!pip install mlxtend```<jupyter_code>import pandas as pd
from sklearn.feature_selection import VarianceThreshold
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
from mlxtend.feature_selection import SequentialFeatureSelector as SFS<jupyter_output><empty_output>
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