done Murkowski distance

p is a parameter that controls the type of distance measure. It determines the "norm" of the distance metric. When 𝑝 = 1 p=1, the formula represents the Manhattan distance, which is the sum of the absolute differences between coordinates. When 𝑝 = 2 p=2, it represents the Euclidean distance, which is the straight-line distance between two points in Euclidean space. For other values of 𝑝 p, it generalizes the distance calculation. For example, higher values of 𝑝 p give more emphasis to larger differences between coordinates. Mathematically: 𝑑 ( 𝑥 , 𝑦 ) = ( ∑ 𝑖 = 1 𝑛 ∣ 𝑥 𝑖 − 𝑦 𝑖 ∣ 𝑝 ) 1 𝑝 d(x,y)=(∑ i=1 n ​ ∣x i ​ −y i ​ ∣ p ) p 1 ​This formulation allows you to adjust how sensitive the distance is to the differences between individual dimensions by changing the value of 𝑝 p.

I learned about Minkowski distance, the ageneralized equation of Manhattan, and Euclidean distance. 𝑝=1 p=1: Emphasizes the sum of the absolute differences (Manhattan). 𝑝=2 p=2: Emphasizes the Euclidean geometric distance. 𝑝→∞ p→∞: Emphasizes the maximum difference in any single dimension (Chebyshev).

Done

Done

I learned in this lecture Minkowski distance.

I learned Minkowski distance.

Discussed, The mathematical solution of Minkowski Distance by the p-value of Euclidean and Manhattan distances.

AOA, I learned in this lecture about how we can find neighbors by distance, which is Minkowski distance ( gernalized form of Euclidean and Manhattan distance ) ALLAH PAK aap ko sahat o aafiat wali lambi umar ata kray aor ap ko dono jahan ki bhalian naseeb farmaey,Ameen.