The cluster.stats () function returns a list that contains many useful components for analyzing the intrinsic properties of a clustering: Let`s start by calculating a cross-table between k-Means clusters and reference labels: an important aspect of the cluster is a formidable contract that covers everything the cluster will share and do for each member. Insurance groups charge registration fees, dues and sometimes maintenance fees and even exit fees. Do research, read reviews, ask current and former members and make sure there are no hidden fees before signing. The SIAA is not in itself an insurance cluster, an aggregator, or a network. SIAA is a national network of 48 master`s agencies in the United States, with nearly 5,000 members who together write $9.1 billion in bonuses. If you decide to join us, you would be a member of one of these master`s agencies that will use their local knowledge, relationships and know-how to help you grow. 4.3 In the event that a party inadvertently and unintentionally requests insurance transactions from an account or another party, if it learns that it is an account of another party, the party will ask to withdraw from the invitation and, since then, notify the party who owns the account. These contracting parties can then enter into all agreements that can be concluded by mutual agreement in their place; However, if the contracting party for which this account is encoded in the BOOKS of the CIS informs the CIS of the terms of the reciprocal agreement, the account remains coded to the original owner of the contracting party. For those who need a little support, market influence and power in numbers and volume, a cluster can be the way to go. It is flexible, easy to set up and can be an excellent solution for the smallest agency that wants help and power, while maintaining its autonomy. There are no two exactly the same cluster agreements, so read the fine print of the contract and then ask questions about cluster practices that go beyond the agreement. Remember that the silhouette coefficient (-(S_i)) measures how similar an object (i) is to other objects in its own cluster compared to those in the neighboring cluster.