A minimum weight spanning tree (MST) connects all vertices in a connected graph with the least total edge weight and no cycles, with Prim’s and Kruskal’s algorithms being common methods to find it. MSTs have applications in image processing, network design, and cluster analysis, providing advantages like simpler network design and cost savings, but also carry disadvantages such as no backup paths and limitations in network types. The document outlines these concepts along with their pros and cons.

1. MINIMUM WEIGHT
SPANNING
TREE
NAME: KT

2. MINIMUM WEIGHT SPANNING TREE
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A minimum weight spanning tree (MST) is
a subset of edges in a connected graph
that connects all vertices without cycles
and has the smallest possible total edge
weight.

3. ALGORITHMS
There are two
algorithms to find
minimum spanning
tree.
1 Prim’s Algorithm
2 Kruskals Algorithm
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4. APPLICATIONS
Image
processing
Network
design
Cluster
Analysis
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5. ADVANTAGES .
& DISADVANTAGES
Here are some advantages
and disadvantages of
minimum weight spanning
tree.
SIMPLER
NETWORK
DESIGN
USEFUL IN
MANY
FIELDS
COST
SAVINGS
NO BACKUP
PATHS
NOT ALWAYS
BEST FOR
EVERY PROBLEM
LIMITED TO
CERTAIN TYPES
OF NETWORK
DISADVANTAGES
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ADVANTAGES

6. THANK YOU
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