Merge pull request rasbt#1057 from tanmaychimurkar/patch-1

Update minor typos in fpgrowth.ipynb

Author: rasbt

docs/sources/user_guide/frequent_patterns/fpgrowth.ipynb

@@ -32,11 +32,11 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "FP-Growth [1] is an algorithm for extracting frequent itemsets with applications in association rule learning that emerged as a popular alternative to the established Apriori algorighm [2]. \n",
+    "FP-Growth [1] is an algorithm for extracting frequent itemsets with applications in association rule learning that emerged as a popular alternative to the established Apriori algorithm [2]. \n",
     "\n",
     "In general, the algorithm has been designed to operate on databases containing transactions, such as purchases by customers of a store. An itemset is considered as \"frequent\" if it meets a user-specified support threshold. For instance, if the support threshold is set to 0.5 (50%), a frequent itemset is defined as a set of items that occur together in at least 50% of all transactions in the database.\n",
     "\n",
-    "In particular, and what makes it different from the Apriori frequent pattern mining algorithm, FP-Growth is an frequent pattern mining algorithm that does not require candidate generation. Internally, it uses a so-called FP-tree (frequent pattern tree) datastrucure without generating the candidate sets explicitely, which makes is particularly attractive for large datasets."
+    "In particular, and what makes it different from the Apriori frequent pattern mining algorithm, FP-Growth is an frequent pattern mining algorithm that does not require candidate generation. Internally, it uses a so-called FP-tree (frequent pattern tree) datastrucure without generating the candidate sets explicitly, which makes it particularly attractive for large datasets."
    ]
   },
   {