addition of unit 1 3 4 5

unit 1/06_Data_Discretization.md

@@ -0,0 +1,27 @@
+# Data Discretization
+
+**Data Discretization** is the process of converting a large number of continuous values into a smaller number of finite intervals (bins).
+
+## Why use it?
+- Makes data easier to understand.
+- Many algorithms work better with categories than infinite numbers.
+
+## Techniques
+
+### 1. Binning
+- Sorting data and dividing it into "bins".
+- **Example**: Grouping ages into [0-10], [11-20], etc.
+- Helps smooth out noise.
+
+### 2. Histogram Analysis
+- Using a bar chart (histogram) to see the distribution and decide where to split the data.
+
+### 3. Cluster Analysis
+- Using clustering (like K-Means) to group similar values, then using those groups as the intervals.
+
+## Concept Hierarchy
+- Organizing data from **low-level** concepts to **high-level** concepts.
+- **Example (Location)**:
+  - Street -> City -> State -> Country.
+- **Top-down Mapping**: General to Specific.
+- **Bottom-up Mapping**: Specific to General.