(defun run-sample-experiment (&key
			      (tbls (list 
				     "data/effort/telecom1.arff.lisp" 
				     "data/effort/kemerer.arff.lisp" 
				     "data/effort/maxwell.arff.lisp" 
				     "data/effort/albrecht.arff.lisp"
				     "data/effort/china.arff.lisp"
				     "data/effort/desharnais_1_1.arff.lisp"
				     "data/effort/finnish.arff.lisp"))
			      (repeats 20)
			      (min-size 6)
			      (crit 97)
			      (treatments (list (list #'row-raw-cells "raw") (list #'row-log-cells "log") (list #'row-cells "norm")))
			      (idea-n (list (list #'idea #'knn) (list #'idea-k2 #'knn-k2)))
			      (k-nearest (list 1 2 4 8)))
  (dolist (tbl tbls)
    (format t "~a~%~%" tbl)
    (let* ((results (make-hash-table))
	   (tbl1 (data tbl)))
      (doitems (treatment i treatments)
	(doitems (k j k-nearest)
	  (doitems (n num idea-n)
	    (let ((key-name (intern (concatenate
			'string
			(second treatment)
			(string "+")
			(write-to-string k)
			(string "+")
			(parse-name (first n))))))
	    (setf (gethash key-name results)
		  (make-effort-results :treatment key-name))))))
      (dotimes (r repeats)
	(multiple-value-bind (train test)
	    (traintest tbl1)
	  (doitems (treatment i treatments)
	    (doitems (k j k-nearest)
	      (doitems (n num idea-n)
		(let* ((log (make-effort-result)))
		  (classify-all1-effort train test log min-size (first treatment) k n)
		  (push (effort-result-mres log) (effort-results-mres (gethash (intern (concatenate
							   'string
							   (second treatment)
							   (string "+")
							   (write-to-string k)
							   (string "+")
							   (parse-name (first n))))
							  results)))))))))
      (let* (list-of-results)
	(dovalues (value results)
	  (push value list-of-results))
	(abccdddd list-of-results)))))
	


;; Take several tables and create ranks and 

(defun classify-multiple-numeric-sets (&key
                               (tbls (list "data/effort/telecom1.arff.lisp" "data/effort/kemerer.arff.lisp" "data/effort/maxwell.arff.lisp" "data/effort/albrecht.arff.lisp" "data/effort/nasa93.arff.lisp" "data/effort/coc81.arff.lisp" "data/effort/desharnais_1_1.arff.lisp" "data/effort/finnish.arff.lisp" "data/effort/china.arff.lisp"))
                               (repeats 20)
                               (k 6))
  ; Create an empty list of "effort-results" structs to pass to (display-effort-results when complete
  (let* ((results))
    (dolist (tbl tbls)
      ; Load table and make an effort-results object to keep MRES from the crossvalidation
      (let* ((tbl1 (data tbl))
             (result (make-effort-results)))
        (setf (effort-results-treatment result) tbl)
	; Repeat repeats times for cross-validation
        (dotimes (r repeats)
	  ; Create a effort-result object the knn learner uses to log results.
          (let* ((log (make-effort-result)))
	    ; Split into train and test sets.
            (multiple-value-bind (train test)
                (traintest tbl1)
	      ; Classify
              (classify-all1-effort train test log k))
	    ; Push the results we get back from the learner onto the effort-results list.
            (push (effort-result-mres log) (effort-results-mres result))))
	; We're finished with this set. Push the results onto a list for consumption by the display-efforts-results function.
        (push result results)))
    ; Display a pretty table for numeric results.
    (display-effort-results results 95 #'mann-whitney)))