The attached data file contains information on electricity costs (Cost) along with average outdoor temperature (Temp), working days per month (Days), and tons of product produced (Tons).

Partition this data using the standard partition function in Data Mining. Use the standard 60% training and 40% validation percentages. Be sure the the random number seed option is selected with 12345 as the seed.

Now run a regression model on the partitioned data to predict Cost from Temp, Days, and Tons. What is the Root Mean Square Error (RMSE) for the training data. (Enter your answer to one decimal place)

Cost	Temp	Days	Tons
16747	46	22	75
7901	31	24	98
13526	67	25	86
11743	43	28	86
29243	100	29	82
8502	57	28	94
19775	76	25	74
23041	71	30	70
15870	23	26	66
15804	60	25	73
9447	28	29	95
23878	78	25	82
16998	72	24	80
10514	22	24	73
23615	50	26	66
15616	70	23	74
16481	89	25	99
14340	33	27	93
15148	30	28	67
20942	55	24	72
14022	71	29	86
28922	75	25	71
6881	52	22	99
7757	30	22	88
18452	82	25	74
18563	38	29	66
14136	83	25	98
10100	33	23	76
22655	91	29	74
11388	41	20	75
12480	30	27	73
10171	28	22	83
8557	29	20	73
24286	69	30	74
11093	36	22	70
32556	65	28	65
8968	62	23	95
10100	63	27	93
10941	79	24	94
15806	43	26	66
15079	40	28	66
11274	72	25	84
18520	80	23	68
17285	45	25	92
20670	85	21	79
16460	62	21	62
26401	98	27	65
15300	41	24	78
13603	43	26	75
11977	52	23	95
29590	89	23	62
14798	60	23	81
9043	30	28	92
12196	60	21	90
14164	59	22	79
22527	70	28	65
17159	89	22	97
16634	91	23	73
11168	46	29	94
19271	44	24	60
6722	22	22	98
27653	85	28	67
12594	76	21	97
20876	76	30	67
24438	97	26	63
14575	23	22	82
12796	45	28	82
10773	97	24	95
10432	52	21	66
8131	63	20	95
9588	46	24	99
14741	51	28	66
20740	91	26	88
10760	63	23	84
17768	81	28	90
12295	38	28	73
8701	71	21	98
20055	96	22	81
8009	44	25	96
11380	56	28	84